Monopulse is a technique for determining the Direction of Arrival (DOA) of a radar echo by comparing the simultaneous signal responses from two or more antenna beams or apertures. Two principal architectures are employed: 1) amplitude-comparison monopulse, and 2) phase-comparison monopulse. For a constrained-size fully and uniformly illuminated aperture, there is no meaningful difference between the DOA angle precision achievable by an amplitude monopulse architecture versus a phase monopulse architecture. DOA angle estimation precision is almost exclusively a function of antenna size, operating wavelength, and SNR, regardless of amplitude versus phase monopulse architectures.
One of the most iconic of radar waveforms is the Linear FM chirp. It is well-behaved and well-understood, and has become the gold standard against which other radar waveforms are measured. It has a number of desirable attributes, but is not without some issues. It may be processed by a number of techniques with many variations. Details of the Linear FM chirp are presented and discussed in this report.
A single Synthetic Aperture Radar (SAR) image is a 2-Dimensional projection of a 3-Dimensional scene, with very limited ability to estimate surface topography. However, with multiple SAR images collected from suitably different geometries, they may be compared with multilateration calculations to estimate characteristics of the missing dimension. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and can be cast as a least-squares exercise. A measure of Dilution of Precision (DOP) can be used to compare the relative merits of various collection geometries.
An aircraft commander needs to be aware of weather phenomena that might be hazardous to his aircraft and mission. An important tool for this is airborne weather (WX) detection radar. The airborne WX radar needs to map weather for the aircraft commander that might be relevant to the safety of the aircraft, which involves both detecting a weather phenomenon, and to some extent seeing through it to detect weather phenomena behind it. Many factors influence the performance of an airborne WX radar
Perhaps no single radar component has a more profound effect on Synthetic Aperture Radar (SAR) performance than the antenna. Especially for spaceborne SAR, one particular common design constraint for the antenna is the minimum antenna area constraint. While useful, it relies on a number of assumptions and approximations that may not always be valid or applicable. Indeed, useful operational systems have been built and flown that do not strictly adhere to this constraint. A closer examination of this constraint yields insights into what the real limitations are, or might be.
Measurements of both long ranges and high velocities pose a contradiction to a pulse-Doppler radar, driving the desired Pulse Repetition Frequency (PRF) in different directions. Often, making one of the measurements unambiguous will make the other ambiguous. The PRF can be adjusted to trade ambiguities in range and velocity, subject to well-defined limits. Various regions of the radar’s operating characteristics in range-velocity space have come to be termed Low-PRF, Medium-PRF, and High-PRF. Selecting a radar operating point, chiefly its PRF, will not only characterize ambiguities that are generated, but also blind ranges and blind velocities. Techniques to mitigate ambiguities and blind regions do exist, allowing substantial extension of the discernable ranges and velocities to the radar.
A fundamental task of radar, beyond merely detecting a target, is to estimate some parameters associated with it. For example, this might include range, direction, velocity, etc. In any case, multiple measurements, often noisy, need to be processed to yield a ‘best estimate’ of the parameter. A common mathematical method for doing so is called “Regression” analysis. The goal is to minimize the expected squared error in the estimate. Even when alternate algorithms are considered, the least squared-error regression analysis is the benchmark against which alternatives are compared.
Synthetic Aperture Radar (SAR) creates imagery of the earth’s surface from airborne or spaceborne radar platforms. However, the nature of any radar is to geolocate its echo data, i.e., SAR images, relative to its own measured radar location. Acceptable accuracy and precision of such geolocation can be quite difficult to achieve, and is limited by any number of parameters. However, databases of geolocated earth imagery do exist, often using other imaging modalities, with Google Earth being one such example. These can often be much more accurate than what might be achievable by the radar itself. Consequently, SAR images may be aligned to some higher accuracy database, thereby improving the geolocation of features in the SAR image. Examples offer anecdotal evidence of the viability of such an approach.
Foliage penetration (FOPEN) radar at lower frequencies (VHF, UHF) is a well-studied area with many contributions. However, there is growing interest in using higher Ku-band frequencies (12-18 GHz) for FOPEN. Specifically, the reduced wavelength sizes provide some key saliencies for developing more optimized detection solutions. The disadvantage is that exploiting Ku-band for FOPEN is complicated because higher frequencies have pronounced scattering effects due to their smaller wavelengths. A methodology h as been developed to model and simulate FOPEN problems that characterize the phenomenology of Ku-band electromagnetic ( EM ) wave transmissions through moderate foliage. The details of this research (i.e. the realistic tree models, simulation setup and results) are documented in multiple reports. The main focus of this report is to describe the preliminary validation and verification of Altair FEKO, the computational EM (CEM) software used for this research, as well as present a simplified symmetrical tree model and an introductory CAD tree model.
Radar is by its basic nature a ranging instrument. If radar range and range-rate measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.
Foliage penetration (FOPEN) radar at lower frequencies (VHF, UHF) is a well-studied area with many contributions. However, there is growing interest in using higher Ku-band frequencies (12-18 GHz) for FOPEN. Specifically, the reduced wavelength sizes provide some key saliencies for developing more optimized detection solutions. The disadvantage is that exploiting Ku-band for FOPEN is complicated because higher frequencies have pronounced scattering effects due to their smaller wavelengths. A methodology has been developed to model and simulate FOPEN problems that characterize the phenomenology of Ku-band EM wave transmissions through moderate foliage. The details of this research are documented in multiple reports. The main focus of this report is to describe the FOPEN model simulation scene setup, validation and results.
Radar is by its basic nature a ranging instrument. If radar range measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with grayscale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with grayscale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
Often a crucial exploitation of a Synthetic Aperture Radar (SAR) image requires accurate and precise knowledge of its geolocation, or at least the geolocation of a feature of interest in the image. However, SAR, like all radar modes of operation, makes its measurements relative to its own location or position. Consequently, it is crucial to understand how the radar's own position and motion impacts the ability to geolocate a feature in the SAR image. Furthermore, accuracy and precision of navigation aids like GPS directly impact the goodness of the geolocation solution.
Synthetic Aperture Radar (SAR) projects a 3-D scene’s reflectivity into a 2-D image. In doing so, it generally focusses the image to a surface, usually a ground plane. Consequently, scatterers above or below the focal/ground plane typically exhibit some degree of distortion manifesting as a geometric distortion and misfocusing or smearing. Limits to acceptable misfocusing define a Height of Focus (HOF), analogous to Depth of Field in optical systems. This may be exacerbated by the radar’s flightpath during the synthetic aperture data collection. It might also be exploited for target height estimation and offer insight to other height estimation techniques.
A stripmap Synthetic Aperture Radar (SAR) image is a long SAR image along some centerline, and formed from multiple synthetic apertures. At issue is that the centerline in the image actually corresponds to an arc on a round earth, and multiple strategies exist for fitting the image centerline to the round earth. Some of those strategies involve Rhumb lines, great circle paths, and great ellipse paths. Some are better than others in polar regions. Notions of parallel flight paths for the radar during data collection also require careful consideration of the geometry of a round earth.
The motivation for this report is to discuss and present some realistic tree models employed in computational electromagnetics (EM) simulations to study foliage penetration (FOPEN) at Ku-band. The detail obtained in these trees is unprecedented in FOPEN modeling since many studies in this area focus on lower frequencies where precise tree parameters are not required due to the associated large wavelengths relative to the tree dimensions. The focus of this study is in the Ku-band range where the wavelength is notably smaller and the details of the trees have more of an influence on EM waves (i.e. scattering, attenuating, reflecting, diffracting etc.). Therefore, explicit tree parameters are modeled. Also, moderate foliage is of most interest because with less dense foliage t here is a higher percentage of Ku-band transmission. The EM wave and foliage interaction s are simulated with the computational electromagnetics (CEM) Altair FEKO software. The realistic tree model s implemented for simulations are created in the computer-aided design (CAD) software Arbaro and the module CADFEKO that is offered in FEKO. Details of these tree models are provided, and EM simulation results will be discussed in a follow-on report
A useful and popular waveform for high-performance radar systems is the Linear Frequency Modulated (LFM) chirp. The chirp may have a positive frequency slope with time (up-chirp) or a negative frequency slope with time (down-chirp). There is no inherent advantage to one with respect to the other, except that the receiver needs to be matched to the proper waveform. However, if up-chirps and down-chirps are employed on different pulses in the same Coherent Processing Interval (CPI), then care must be taken to maintain coherence in the range-compressed echo signals. We present the mathematics for doing so, for both correlation processing and stretch processing.
Once a Synthetic Aperture Radar (SAR) image is formed, the natural question then is, "Where is this image?" and/or "Where exactly is this feature displayed in the image?" Thus, geolocation is an important exploitation of the SAR image. Since SAR measures relative location to its own position, it is crucial to understand how the radars position and motion imp acts the ability to geolocate a feature in the SAR image. Furthermore, accuracy and precision of navigation aids like GPS directly impact the goodness of the geolocation solution. These relationships are developed and discussed.
Modern high-performance radar systems are employing ever-more Digital Signal Processing (DSP), replacing ever-more formerly analog components. Precisely predicting the performance of digital filters and correlators requires an awareness of some of the finer points and characteristics of digital filters. We examine a representative radar receiver DSP chain that is processing a Linear Frequency Modulated (LFM) chirp.
The physical separation of the transmitter from the receiver into perhaps separate flight vehicles (with separate flight paths) in a bistatic Synthetic Aperture radar system adds considerable complexity to an already complex system. Synchronization of waveform parameters and timing attributes become problematic, and notions of even the synthetic aperture itself take on a new level of abstractness. Consequently, a high-performance, fine-resolution, and reliable bistatic SAR system really needs to be engineered from the ground up, with tighter specifications on a number of parameters, and entirely new functionality in other areas. Nevertheless, such a bistatic SAR system appears viable.
High-performance spotlight Synthetic Aperture Radar (SAR) requires measurement of the radars motion during the synthetic aperture. A convenient coordinate frame for motion measurement is often not the convenient coordinate frame for motion compensation during the SAR data generation and image formation processing. A convenient frame for radar motion measurement is the Earth-Centered Earth-Fixed (ECEF) coordinate frame, whereas spotlight SAR processing typically require s polar coordinates from a selected Scene Reference Point (SRP). This report presents the conversion from ECEF coordinates to appropriate parameters for SAR processing.
A useful performance metric for Intelligence, Surveillance, and Reconnaissance (ISR) radar systems is the Impulse Response (IPR). This is true for a fidelity metric for the signal channel, as well as a stability measure across multiple pulses. The IPR represents performance with respect to both amplitude and phase modulations of the transfer function for components, circuits, subassemblies, and even the looped radar hardware. The proper IPR performance specification limits will depend on radar operating mode. Generally, it will be the intersection of the strictest requirements.
One of the earliest applications for radar was to search for and find maritime vessels on the open sea. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. -
Traditional dual-channel phase-monopulse and amplitude-monopulse antenna systems might electrically steer their difference-channel nulls by suitably adjusting characteristics of their constituent beams or lobes. A phase-monopulse systems' null might be steered by applying suitable relative phase shifts. An amplitude-monopulse systems' null might be steered by applying a suitable relative beam amplitude scaling. The steering of the null might be employed by a continuously mechanically-scanning antenna to stabilize the null direction over a series of radar pulses.
A principal performance-enabling, or performance-limiting, component of Ground-Moving-Target-Indication (GMTI) radar systems is the antenna. Undesired clutter leakage into antenna sidelobes can be particularly problematic, generating undesired false alarms. GMTI system antennas can be designed with characteristics and features to allow discriminating and depressing/suppressing problematic sidelobe leakage of clutter and other undesired signals. We offer analysis and design guidelines for doing so.
Once Synthetic Aperture Radar (SAR) images are formed, they typically need to be stored in some file format which might restrict the dynamic range of what can be represented. Thereafter, for exploitation by human observers, the images might need to be displayed in a manner to reveal the subtle scene reflectivity characteristics the observer seeks, which generally requires further manipulation of dynamic range. Proper image scaling, for both storage and for display, to maximize the perceived dynamic range of interest to an observer depends on many factors, and an understanding of underlying data characteristics. While SAR images are typically rendered with gray-scale, or at least monochromatic intensity variations, color might also be usefully employed in some cases. We analyze these and other issues pertaining to SAR image scaling, dynamic range, radiometric calibration, and display.
The image below is a false-color rendering of a previously published cross-track stereo Synthetic Aperture Radar (SAR) height map. A gray-scale version of this image appeared in the following UUR document.
Phase noise is the instability of an oscillator/clock signal source with respect to frequency and phase. It is an undesirable but unavoidable characteristic that adversely affects the performance of range-Doppler radar systems, including Synthetic Aperture Radar (SAR) and Ground-Moving Target Indicator (GMTI) radar. In short, phase noise effects cannot be neglected in high performance radar designs, will limit performance, and should influence design approaches.
When radar receivers employ multiple channels, the general intent is for the receive channels to be as alike as possible, if not as ideal as possible. This is usually done via prudent hardware design, supplemented by system calibration. Towards this end, we require a quality metric for ascertaining the goodness of a radar channel, and the degree of match to sibling channels. We propose a relevant and usable metric to do just that. Acknowledgements: This report was the result of an unfunded research and development activity.
Simple motion models for complex motion environments are often not adequate for keeping radar data coherent. Eve n perfect motion samples appli ed to imperfect models may lead to interim calculations e xhibiting errors that lead to degraded processing results. Herein we discuss a specific i ssue involving calculating motion for groups of pulses, with measurements only available at pulse-group boundaries. - 4 - Acknowledgements This report was funded by General A tomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Re search and Development Agre ement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affilia te of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and rel ated mission systems, includin g the Predator(r)/Gray Eagle(r)-series and Lynx(r) Multi-mode Radar.
Conventional signal processing to estimate radar Doppler frequency often assumes uniform pulse/sample spacing. This is for the convenience of t he processing. More recent performance enhancements in processor capability allow optimally processing nonuniform pulse/sample spacing, thereby overcoming some of the baggage that attends uniform sampling, such as Doppler ambiguity and SNR losses due to sidelobe control measures.
Window taper functions of finite apertures are well-known to control undesirable sidelobes, albeit with performance trades. A plethora of various taper functions have been developed over the years to achieve various optimizations. We herein catalog a number of window functions, and com pare principal characteristics.
Spurious energy in received radar data is unanticipated and undesired signal relevant to radar target signatures, usually a consequence of nonideal component and circuit behavior, perhaps due to I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), or other sources. The manifestation of the spurious energy in a range-Doppler map or image can often be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images having been processed with the same data but different signal paths and modulations allows identifying undesired spurs and then cropping or apodizing them.
It is often advantageous to modify, or warp, radar waveforms, particularly with respect to group-delay and spectral dilation. These warping adjustments may facilitate real-time motion compensation of waveforms in radar systems, especially when those waveforms are generated by a digital parametric waveform generator. Relevant waveforms to this paper include Frequency Modulated (FM) waveforms, such as the Linear-FM (LFM) chirp, Non-Linear FM (NLFM) chirp, and other general FM waveforms. We present techniques for making fine adjustments to dynamically warp general FM waveforms.
An important characteristic of a radar receiver is the noise level within the receiver chain. The common parameter that specifies this is the System Noise Factor, which depends on system design and may vary with gain settings, temperature, and other factors. A modified Y-factor technique is detailed to calculate System Noise Factor for a radar receiver. Error sources are also detailed.
Antenna apertures that are tapered for sidelobe control can also be parsed into subapertures for Direction of Arrival (DOA) measurements. However, the aperture tapering complicates phase center location for the subapertures, knowledge of which is critical for proper DOA calculation. In addition, tapering affects subaperture gains, making gain dependent on subaperture position. Techniques are presented to calculate subaperture phase center locations, and algorithms are given for equalizing subapertures’ gains. Sidelobe characteristics and mitigation are also discussed.
Conventional beam-shaping for array antennas is accomplished via an amplitude-taper on the elemental radiators. It is well known that proper manipulation of the elemental phases can also shape the antenna far-field pattern. A fairly simple transformation from a desired amplitude-taper to a phase-taper can yield nearly equivalent results.
Typically, when three or more antenna beams along a single axis are required, the answer has been multiple antenna phase-centers, essentially a phase-monopulse system. Such systems and their design parameters are well-reported in the literature. Less appreciated is that three or more antenna beams can also be generated in an amplitude-monopulse fashion. Consequently, design guidelines and performance analysis of such antennas is somewhat under-reported in the literature. We provide discussion herein of three beams arrayed in a single axis with an amplitude-monopulse configuration.
Complex pixel values for Synthetic Aperture Radar (SAR) images of uniform distributed clutter can be represented as either real/imaginary (also known as I/Q) values, or as Magnitude/Phase values. Generally, these component values are integers with limited number of bits. For clutter energy well below full-scale, Magnitude/Phase offers lower quantization noise than I/Q representation. Further improvement can be had with companding of the Magnitude value.
Ground Moving Target Indicator (GMTI) radar attempts to detect and locate targets with unknown motion. Very slow-moving targets are difficult to locate in the presence of surrounding clutter. This necessitates multiple antenna phase centers (or equivalent) to offer independent Direction of Arrival (DOA) measurements. DOA accuracy and precision generally remains dependent on target Signal-to-Noise Ratio (SNR), Clutter-toNoise Ratio (CNR), scene topography, interfering signals, and a number of antenna parameters. This is true even for adaptive techniques like Space-Time-AdaptiveProcessing (STAP) algorithms.
Multi-aperture or multi-subaperture antennas are fundamental to Ground Moving Target Indicator (GMTI) radar systems in order to detect slow-moving targets with Doppler characteristics similar to clutter. Herein we examine the performance of several subaperture architectures for their clutter cancelling performance. Significantly, more antenna phase centers isn’t always better, and in fact is sometimes worse, for detecting targets.
Technological and doctrinal surprise is about rendering preparations for conflict as irrelevant or ineffective . For a sensor, this means essentially rendering the sensor as irrelevant or ineffective in its ability to help determine truth. Recovery from this sort of surprise is facilitated by flexibility in our own technology and doctrine. For a sensor, this mean s flexibility in its architecture, design, tactics, and the designing organizations ' processes. - 4 - Acknowledgements This report is the result of a n unfunded research and development activity . Sandia National Laboratories is a multi - program laboratory manage d and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000.
High-performance radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. System nonlinearities generate harmonic spurs that at best degrade, and at worst generate false target detections. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this paper the relationship of INL to radar performance; in particular its manifestation in a range-Doppler map or image.
Radar Intelligence, Surveillance, and Reconnaissance (ISR) does not always involve cooperative or even friendly environments or targets. The environment in general, and an adversary in particular, may offer numerous characteristics and impeding techniques to diminish the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the Electromagnetic (EM) signals required by the radar sensor. Consequently mitigation techniques are often prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.
Synthetic Aperture Radar (SAR) measures radar soundings from a set of locations typically along the flight path of a radar platform vehicle. Optimal focusing requires precise knowledge of the sounding source locations in 3-D space with respect to the target scene. Even data driven focusing techniques (i.e. autofocus) requires some degree of initial fidelity in the measurements of the motion of the radar. These requirements may be quite stringent especially for fine resolution, long ranges, and low velocities. The principal instrument for measuring motion is typically an Inertial Measurement Unit (IMU), but these instruments have inherent limi ted precision and accuracy. The question is %22How good does an IMU need to be for a SAR across its performance space?%22 This report analytically relates IMU specifications to parametric requirements for SAR. - 4 - Acknowledgements Th e preparation of this report is the result of a n unfunded research and development activity . Although this report is an independent effort, it draws heavily from limited - release documentation generated under a CRADA with General Atomics - Aeronautical System, Inc. (GA - ASI), and under the Joint DoD/DOE Munitions Program Memorandum of Understanding. Sandia National Laboratories is a multi - program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of En ergy's National Nuclear Security Administration under contract AC04-94AL85000.
The linear ground distance per unit time and ground area covered per unit time of producing synthetic aperture radar (SAR) imagery, termed rate of advance (ROA) and area coverage rate (ACR), are important metrics for platform and radar performance in surveillance applications. These metrics depend on many parameters of a SAR system such as wavelength, aircraft velocity, resolution, antenna beamwidth, imaging mode, and geometry. Often the effects of these parameters on rate of advance and area coverage rate are non-linear. This report addresses the impact of different parameter spaces as they relate to rate of advance and area coverage rate performance.
Direction of Arrival (DOA) measurements, as with a monopulse antenna, can be compared against Doppler measurements in a Synthetic Aperture Radar ( SAR ) image to determine an aircraft's forward velocity as well as its crab angle, to assist the aircraft's navigation as well as improving high - performance SAR image formation and spatial calibration.
In modern multi-sensor multi-mode Intelligence, Surveillance, and Reconnaissance (ISR) platforms, the plethora of options available to a sensor/payload operator are quite large, leading to an over-worked operator often down-selecting to favorite sensors and modes. For example, Full Motion Video (FMV) is justifiably a favorite sensor at the expense of radar modes, even if radar modes can offer unique and advantageous information. The challenge is then to increase the utilization of the radar modes in a manner attractive to the sensor/payload operator. We propose that this is best accomplished by combining sensor modes and displays into ‘super-modes’.
Wideband radar systems, especially those that operate at lower frequencies such as VHF and UHF, are often restricted from transmitting within or across specific frequency bands in order to prevent interference to other spectrum users. Herein we describe techniques for notching the transmitted spectrum of a generated and transmitted radar waveform. The notches are fully programmable as to their location, and techniques are given that control the characteristics of the notches.
Radar operation, particularly Ground Moving Target Indicator (GMTI) radar modes, are very sensitive to anomalous effects of system nonlinearities. These throw off harmonic spurs that are sometimes detected as false alarms. One significant source of nonlinear behavior is the Analog to Digital Converter (ADC). One measure of its undesired nonlinearity is its Integral Nonlinearity (INL) specification. We examine in this report the relationship of INL to GMTI performance.
Median filtering reduces speckle in synthetic aperture radar (SAR) imagery while preserving edges, at the expense of coarsening the resolution, by replacing the center pixel of a sliding window by the median value. For shadow detection, this approach helps distinguish shadows from clutter more easily, while preserving shadow shape delineations. However, the nonlinear operation alters the shadow and clutter distributions and statistics, which must be taken into consideration when computing probability of detection and false alarm metrics. Depending on system parameters, median filtering can improve probability of detection and false alarm by orders of magnitude. Herein, we examine shadow probability of detection and false alarm in a homogeneous, ideal clutter background after median filter post-processing. Some comments on multi-look processing effects with and without median filtering are also made.
Spurious energy in received radar data is a consequence of nonideal component and circuit behavior. This might be due to I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), or other sources. The manifestation of the spurious energy in a range-Doppler map or image can be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images having been processed with the same data but different signal paths and modulations allows identifying undesired spurs and then cropping or apodizing them.
Radar ISR does not always involve cooperative or even friendly targets. An adversary has numerous techniques available to him to counter the effectiveness of a radar ISR sensor. These generally fall under the banner of jamming, spoofing, or otherwise interfering with the EM signals required by the radar sensor. Consequently mitigation techniques are prudent to retain efficacy of the radar sensor. We discuss in general terms a number of mitigation techniques.
Synthetic Aperture Radar (SAR) performance testing and estimation is facilitated by observing the system response to known target scene elements. Trihedral corner reflectors and other canonical targets play an important role because their Radar Cross Section (RCS) can be calculated analytically. However, reflector orientation and the proximity of the ground and mounting structures can significantly impact the accuracy and precision with which measurements can be made. These issues are examined in this report.
When multiple channels are employed in a pulse-Doppler radar, achieving and maintaining balance between the channels is problematic. In some circumstances the channels may be commutated to achieve adequate balance. Commutation is the switching, trading, toggling, or multiplexing of the channels between signal paths. Commutation allows modulating the imbalance energy away from the balanced energy in Doppler, where it can be mitigated with filtering.
Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFI Filtering (ARF).
It is well known that the spectrum of a signal can be calculated with a Discrete Fourier Transform (DFT), where best resolution is achieved by processing the entire data set. However, in some situations it is advantageous to use a staged approach, where data is first processed within subapertures, and the results are then combined and further processed to a final result. An artifact of this approach is the creation of grating lobes in the final response. The nature of the grating lobes, including their amplitude and spacing, is an artifact of window taper functions, subaperture offsets, and subaperture processing parameters. We assess these factors and exemplify their effects.
The "location" of the radar is the reference location to which the radar measures range. This is typically the antenna's "phase center". However, the antenna's phase center is not generally obvious, and may not correspond to any seemingly obvious physical location, such as the focal point of a dish reflector. This report calculates the phase center of an offset-fed dish reflector antenna.
The performance of an Inverse Synthetic Aperture Radar (ISAR) system depends on a variety of factors, many which are interdependent in some manner. In this report we specifically examine ISAR as applied to maritime targets (e.g. ships). It is often difficult to get your arms around the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall ISAR system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the seek time.
Backprojection has long been applied to SAR image formation. It has equal utility in forming the range-velocity maps for Ground Moving Target Indicator (GMTI) radar processing. In particular, it overcomes the problem of targets migrating through range resolution cells.
The earth's atmosphere affects the velocity of propagation of microwave signals. This imparts a range error to radar range measurements that assume the typical simplistic model for propagation velocity. This range error is a function of atmospheric constituents, such as water vapor, as well as the geometry of the radar data collection, notably altitude and range. Models are presented for calculating atmospheric effects on radar range measurements, and compared against more elaborate atmospheric models.
Polarimetric synthetic aperture radar (SAR) has been used for a variety of dual-use research applications since the 1940's. By measuring the direction of the electric field vector from radar echoes, polarimetry may enhance an analyst's understanding of scattering effects for both earth monitoring and tactical surveillance missions. Polarimetry may provide insight into surface types, materials, or orientations for natural and man-made targets. Polarimetric measurements may also be used to enhance the contrast between scattering surfaces such as man-made objects and their surroundings. This report represents an initial assessment of the utility of, and applications for, polarimetric SAR at Ku-band for airborne or unmanned aerial systems.
The earth isn't flat, and radar beams don't travel straight. This becomes more noticeable as range increases, particularly at shallow depression/grazing angles. This report explores models for characterizing this behavior.
The Signal-to-Noise Ratio (SNR) of a radar echo signal will vary across a range swath, due to spherical wavefront spreading, atmospheric attenuation, and antenna beam illumination. The antenna beam illumination will depend on antenna pointing. Calculations of geometry are complicated by the curved earth, and atmospheric refraction. This report investigates optimizing antenna pointing to maximize the minimum SNR across the range swath.
Proper waveform parameter selection allows collecting Synthetic Aperture Radar (SAR) phase history data on a rotated grid in the Fourier Space of the scene being imaged. Subsequent image formation preserves the rotated geometry to allow SAR images to be formed at arbitrary rotation angles without the use of computationally expensive interpolation or resampling operations. This should be useful where control of image orientation is desired such as generating squinted stripmaps and VideoSAR applications, among others.
In high-power microwave power amplifiers for radar, distortion in both amplitude and phase should generally be expected. Phase distortions can be readily equalized. Some amplitude distortions are more problematic than others. In general, especially for SAR using LFM chirps, low frequency modulations such as gain slopes can be tolerated much better than multiple cycles of ripple across the passband of the waveform.
A horn-fed dish reflector antenna has characteristics including beam pattern that are a function of its mechanical form. The beam pattern can be altered by changing the mechanical configuration of the antenna. One way to do this is with a reflecting insert or shim added to the face of the original dish.
The purpose of this report is to provide a background to Synthetic Aperture Radar (SAR) image formation using the Polar Format (PFA) processing algorithm. This is meant to be an aid to those tasked to implement real-time image formation using the Polar Format processing algorithm.
The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'.
Doppler radars can distinguish targets from clutter if the target's velocity along the radar line of sight is beyond that of the clutter. Some targets of interest may have a Doppler shift similar to that of clutter. The nature of sea clutter is different in the clutter and exo-clutter regions. This behavior requires special consideration regarding where a radar can expect to find sea-clutter returns in Doppler space and what detection algorithms are most appropriate to help mitigate false alarms and increase probability of detection of a target. This paper studies the existing state-of-the-art in the understanding of Doppler characteristics of sea clutter and scattering from the ocean to better understand the design and performance choices of a radar in differentiating targets from clutter under prevailing sea conditions.
A Linear Frequency-Modulated (LFM) chirp is a function with unit amplitude and quadratic phase characteristic. In a focused Synthetic Aperture Radar (SAR) image, a residual chirp is undesired for targets of interest, as it coarsens the manifested resolution. However, for undesired spurious signals, a residual chirp is often advantageous because it spreads the energy and thereby diminishes its peak value. In either case, a good understanding of the effects of a residual LFM chirp on a SAR Impulse Response (IPR) is required to facilitate system analysis and design. This report presents an analysis of the effects of a residual chirp on the IPR. As reference, there is a rich body of publications on various aspects of LFM chirps. A quick search reveals a plethora of articles, going back to the early 1950s. We mention here purely as trivia one of the earlier analysis papers on this waveform by Klauder, et al.
Trihedral corner reflectors are the preferred canonical target for SAR performance evaluation for many radar development programs. The conventional trihedrals have problems with substantially reduced Radar Cross Section (RCS) at low grazing angles, unless they are tilted forward, but in which case other problems arise. Consequently there is a need for better low grazing angle performance for trihedrals. This is facilitated by extending the bottom plate. A relevant analysis of RCS for an infinite ground plate is presented. Practical aspects are also discussed.
Ground Moving Target Indicator (GMTI) radar maps echo data to range and range-rate, which is a function of a moving target's velocity and its position within the antenna beam footprint. Even stationary clutter will exhibit an apparent motion spectrum and can interfere with moving vehicle detections. Consequently it is very important for a radar to understand how stationary clutter maps into radar measurements of range and velocity. This mapping depends on a wide variety of factors, including details of the radar motion, orientation, and the 3-D topography of the clutter.
Angular orientation errors of the real antenna for Synthetic Aperture Radar (SAR) will manifest as undesired illumination gradients in SAR images. These gradients can be measured, and the pointing error can be calculated. This can be done for single images, but done more robustly using multi-image methods. Several methods are provided in this report. The pointing error can then be fed back to the navigation Kalman filter to correct for problematic heading (yaw) error drift. This can mitigate the need for uncomfortable and undesired IMU alignment maneuvers such as S-turns.
Demand is increasing for imaging ships at sea. Conventional SAR fails because the ships are usually in motion, both with a forward velocity, and other linear and angular motions that accompany sea travel. Because the target itself is moving, this becomes an Inverse- SAR, or ISAR problem. Developing useful ISAR techniques and algorithms is considerably aided by first understanding the nature and characteristics of ship motion. Consequently, a brief study of some principles of naval architecture sheds useful light on this problem. We attempt to do so here. Ship motions are analyzed for their impact on range-Doppler imaging using Inverse Synthetic Aperture Radar (ISAR). A framework for analysis is developed, and limitations of simple ISAR systems are discussed.
Synthetic Aperture Radar (SAR) performance testing and estimation is facilitated by observing the system response to known target scene elements. Trihedral corner reflectors and other canonical targets play an important role because their Radar Cross Section (RCS) can be calculated analytically. However, reflector orientation and the proximity of the ground and mounting structures can significantly impact the accuracy and precision with which measurements can be made. These issues are examined in this report.
A principal measure of Synthetic Aperture Radar (SAR) image quality is the manifestation in the SAR image of a spatial impulse, that is, the SAR's Impulse Response (IPR). IPR requirements direct certain design decisions in a SAR. Anomalies in the IPR can point to specific anomalous behavior in the radar's hardware and/or software.
Computed Tomography (CT) is a well established technique, particularly in medical imaging, but also applied in Synthetic Aperture Radar (SAR) imaging. Basic CT imaging via back-projection is treated in many texts, but often with insufficient detail to appreciate subtleties such as the role of non-uniform sampling densities. Herein are given some details often neglected in many texts.
Coherent Change Detection (CCD) with Synthetic Aperture Radar (SAR) images is a technique whereby very subtle temporal changes can be discerned in a target scene. However, optimal performance requires carefully matching data collection geometries and adjusting the processing to compensate for imprecision in the collection geometries. Tolerances in the precision of the data collection are discussed, and anecdotal advice is presented for optimum CCD performance. Processing considerations are also discussed.
Nonlinear FM (NLFM) waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM (LFM) waveform with equivalent sidelobe filtering. This report presents details of processing NLFM waveforms in both range and Doppler dimensions, with special emphasis on compensating intra-pulse Doppler, often cited as a weakness of NLFM waveforms.
Pulsed Radar systems suffer range ambiguities, that is, echoes from pulses transmitted at different times arrive at the receiver simultaneously. Conventional mitigation techniques are not always adequate. However, pulse modulation schemes exist that allow separation of ambiguous ranges in Doppler space, allowing easy filtering of problematic ambiguous ranges.
Wideband radar signals are problematic for phased array antennas. Wideband radar signals can be generated from series or groups of narrow-band signals centered at different frequencies. An equivalent wideband LFM chirp can be assembled from lesser-bandwidth chirp segments in the data processing. The chirp segments can be transmitted as separate narrow-band pulses, each with their own steering phase operation. This overcomes the problematic dilemma of steering wideband chirps with phase shifters alone, that is, without true time-delay elements.
Nonlinear FM waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM waveform with equivalent sidelobe filtering. This report presents design and implementation techniques for Nonlinear FM waveforms.
The effects of a non-uniform antenna beam are sometimes visible in Synthetic Aperture Radar (SAR) images. This might be due to near-range operation, wide scenes, or inadequate antenna pointing accuracy. The effects can be mitigated in the SAR image by fitting very a simple model to the illumination profile and compensating the pixel brightness accordingly, in an automated fashion. This is accomplished without a detailed antenna pattern calibration, and allows for drift in the antenna beam alignments.
The performance of a Synthetic Aperture Radar (SAR) system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to ''get your arms around'' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics, no matter how bright the engineer tasked to generate a system design. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall SAR system. For example, there are definite optimum frequency bands that depend on weather conditions and range, and minimum radar PRF for a fixed real antenna aperture dimension is independent of frequency. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the ''seek time''.
Limitations on focused scene size for the Polar Format Algorithm (PFA) for Synthetic Aperture Radar (SAR) image formation are derived. A post processing filtering technique for compensating the spatially variant blurring in the image is examined. Modifications to this technique to enhance its robustness are proposed.
Traditional polar format image formation for Synthetic Aperture Radar (SAR) requires a large amount of processing power and memory in order to accomplish in real-time. These requirements can thus eliminate the possible usage of interpreted language environments such as MATLAB. However, with trapezoidal aperture phase history collection and changes to the traditional polar format algorithm, certain optimizations make MATLAB a possible tool for image formation. Thus, this document's purpose is two-fold. The first outlines a change to the existing Polar Format MATLAB implementation utilizing the Chirp Z-Transform that improves performance and memory usage achieving near realtime results for smaller apertures. The second is the addition of two new possible image formation options that perform a more traditional interpolation style image formation. These options allow the continued exploration of possible interpolation methods for image formation and some preliminary results comparing image quality are given.
Sandia National Laboratories designs and builds Synthetic Aperture Radar (SAR) systems capable of forming high-quality exceptionally fine resolution images. During the spring of 2004 a series of test flights were completed with a Ka-band testbed SAR on Sandia's DeHavilland DHC-6 Twin Otter aircraft. A large data set was collected including real-time fine-resolution images of a variety of target scenes. This paper offers a sampling of high quality images representative of the output of Sandia's Ka-band testbed radar with resolutions as fine as 4 inches. Images will be annotated with descriptions of collection geometries and other relevant image parameters.
Airborne synthetic aperture radar (SAR) imaging systems have reached a degree of accuracy and sophistication that requires the validity of the free-space approximation for radio-wave propagation to be questioned. Based on the thin-lens approximation, a closed-form model for the focal length of a gravity wave-modulated refractive-index interface in the lower troposphere is developed. The model corroborates the suggestion that mesoscale, quasi-deterministic variations of the clear-air radio refractive-index field can cause diffraction patterns on the ground that are consistent with reflectivity artifacts occasionally seen in SAR images, particularly in those collected at long ranges, short wavelengths, and small grazing angles.
SAR phase history data represents a polar array in the Fourier space of a scene being imaged. Polar Format processing is about reformatting the collected SAR data to a Cartesian data location array for efficient processing and image formation. In a real-time system, this reformatting or ''re-gridding'' operation is the most processing intensive, consuming the majority of the processing time; it also is a source of error in the final image. Therefore, any effort to reduce processing time while not degrading image quality is valued. What is proposed in this document is a new way of implementing real-time polar-format processing through a variation on the traditional interpolation/2-D Fast Fourier Transform (FFT) algorithm. The proposed change is based upon the frequency scaling property of the Fourier Transform, which allows a post azimuth FFT interpolation. A post azimuth processing interpolation provides overall benefits to image quality and potentially more efficient implementation of the polar format image formation process.
Relatively small motion measurement errors manifest themselves principally as a phase error in Synthetic Aperture Radar (SAR) complex data samples, and if large enough become observable as a smearing, blurring, or other degradation in the image. The phase error function can be measured and then deconvolved from the original data to compensate for the presumed motion error, ultimately resulting in a well-focused image. Techniques that do this are termed 'autofocus' algorithms. A very popular autofocus algorithm is the Phase Gradient Autofocus (PGA) algorithm. The nearly universal, and typically reasonable, assumption is that the motion errors are less than the range resolution of the radar, allowing solely a phase correction to suffice. Very large relative motion measurement errors manifest themselves as an unexpected additional shifting or migration of target locations beyond any deterministic migration during the course of the synthetic aperture. Degradation in images from data exhibiting errors of this magnitude are substantial, often rendering the image completely useless. When residual range migration due to either real or apparent motion errors exceeds the range resolution, conventional autofocus algorithms fail. Excessive residual migration is increasingly encountered as resolutions become finer, less expensive inertial sensors are used, and operating ranges become longer (due to atmospheric phenomena). A new migration-correction autofocus algorithm has been developed that estimates the excessive residual migration and applies phase and frequency corrections to properly focus the image. This overcomes the conventional constraint that motion errors not exceed the SAR range resolution.
When residual range migration due to either real or apparent motion errors exceeds the range resolution, conventional autofocus algorithms fail. A new migration-correction autofocus algorithm has been developed that estimates the migration and applies phase and frequency corrections to properly focus the image.
Brief disclosures may often be sufficient for the filing of a Technical Advance with Sandia's Intellectual Property Center, but still be inadequate to facilitate an optimum patent application where more detail and explanation are required. Consequently, the crafting of a patent application may require considerably more additional interaction between the application preparer and the inventors. This inefficiency can be considerably mitigated if the inventors address some critical aspects of a patent application when they write a technical report.
Modern high-performance Synthetic Aperture Radar (SAR) systems have evolved into highly versatile, robust, and reliable tactical sensors, offering images and information not available from other sensor systems. For example, real-time images are routinely formed by the Sandia-designed General Atomics (AN/APY-8) Lynx SAR yielding 4-inch resolution at 25 km range (representing better than arc-second resolutions) in clouds, smoke, and rain. Sandia's Real-Time Visualization (RTV) program operates an Interferometric SAR (IFSAR) system that forms three dimensional (3-D) topographic maps in near real-time with National Imagery and Mapping Agency (MIMA) Digital Terrain Elevation Data (DTED) level 4 performance (3 meter post spacing with 0.8-meter height accuracy) or better. When exported to 3-D rendering software, this data allows remarkable interactive fly-through experiences. Coherent Change Detection (CCD) allows detecting tire tracks on dirt roads, foot-prints, and other minor, otherwise indiscernible ground disturbances long after their originators have left the scene. Ground Moving Target Indicator (GMTI) radar modes allow detecting and tracking moving vehicles. A Sandia program known as "MiniSAR" is developing technologies that are expected to culminate in a fully functioning, high-performance, real-time SAR that weighs less than 20 Ibs. The purpose of this paper is to provide an overview of recent technology developments, as well as current on-going research and development efforts at Sandia National Laboratories.
The state-of-the-art of inertial micro-sensors (gyroscopes and accelerometers) has advanced to the point where they are displacing the more traditional sensors in many size, power, and/or cost-sensitive applications. A factor limiting the range of application of inertial micro-sensors has been their relatively poor bias stability. The incorporation of an integral sensitive axis rotation capability would enable bias mitigation through proven techniques such as indexing, and foster the use of inertial micro-sensors in more accuracy-sensitive applications. Fabricating the integral rotation mechanism in MEMS technology would minimize the penalties associated with incorporation of this capability, and preserve the inherent advantages of inertial micro-sensors.
Data collection for interferometric synthetic aperture radar (IFSAR) mapping systems currently utilize two operation modes. A single-antenna, dual-pass IFSAR operation mode is the first mode in which a platform carrying a single antenna traverses a flight path by the scene of interest twice collecting data. A dual-antenna, single-pass IFSAR operation mode is the second mode where a platform possessing two antennas flies past the scene of interest collecting data. There are advantages and disadvantages associated with both of these data collection modes. The single-antenna, dual-pass IFSAR operation mode possesses an imprecise knowledge of the antenna baseline length but allows for large antenna baseline lengths. This imprecise antenna baseline length knowledge lends itself to inaccurate target height scaling. The dual-antenna, one-pass IFSAR operation mode allows for a precise knowledge of the limited antenna baseline length but this limited baseline length leads to increased target height noise. This paper presents a new, innovative dual-antenna, dual-pass IFSAR operation mode which overcomes the disadvantages of the two current IFSAR operation modes. Improved target height information is now obtained with this new mode by accurately estimating the antenna baseline length between the dual flight passes using the data itself. Consequently, this new IFSAR operation mode possesses the target height scaling accuracies of the dual-antenna, one-pass operation mode and the height-noise performance of the one-antenna, dual-pass operation mode.
An Interferometric Moving Target Indicator radar can be used to measure the tangential velocity component of a moving target. Multiple baselines, along with the conventional radial velocity measurement, allow estimating the true 3-D velocity vector of a target.
Imaging systems such as Synthetic Aperture Radar collect band-limited data from which an image of a target scene is rendered. The band-limited nature of the data generates sidelobes, or ''spilled energy'' most evident in the neighborhood of bright point-like objects. It is generally considered desirable to minimize these sidelobes, even at the expense of some generally small increase in system bandwidth. This is accomplished by shaping the spectrum with window functions prior to inversion or transformation into an image. A window function that minimizes sidelobe energy can be constructed based on prolate spheroidal wave functions. A parametric design procedure allows doing so even with constraints on allowable increases in system bandwidth. This approach is extended to accommodate spectral notches or holes, although the guaranteed minimum sidelobe energy can be quite high in this case. Interestingly, for a fixed bandwidth, the minimum-mean-squared-error image rendering of a target scene is achieved with no windowing at all (rectangular or boxcar window).
A Synthetic Aperture Radar (SAR) image is a two-dimensional projection of the radar reflectivity from a 3-dimensional object or scene. Stereoscopic SAR employs two SAR images from distinct flight paths that can be processed together to extract information of the third collapsed dimension (typically height) with some degree of accuracy. However, more than two SAR images of the same scene can similarly be processed to further improve height accuracy, and hence 3-dimensional position accuracy. This report shows how.
Superresolution concepts offer the potential of resolution beyond the classical limit. This great promise has not generally been realized. In this study we investigate the potential application of superresolution concepts to synthetic aperture radar. The analytical basis for superresolution theory is discussed. The application of the concept to synthetic aperture radar is investigated as an operator inversion problem. Generally, the operator inversion problem is ill posed. A criterion for judging superresolution processing of an image is presented.
Interferometric SAR (IFSAR) can be shown to be a special case of 3-D SAR image formation. In fact, traditional IFSAR processing results in the equivalent of merely a super-resolved, under-sampled, 3-D SAR image. However, when approached as a 3-D SAR problem, a number of IFSAR properties and anomalies are easily explained. For example, IFSAR decorrelation with height is merely ordinary migration in 3-D SAR. Consequently, treating IFSAR as a 3-D SAR problem allows insight and development of proper motion compensation techniques and image formation operations to facilitate optimal height estimation. Furthermore, multiple antenna phase centers and baselines are easily incorporated into this formulation, providing essentially a sparse array in the elevation dimension. This paper shows the Polar Format image formation algorithm extended to 3 dimensions, and then proceeds to apply it to the IFSAR collection geometry. This suggests a more optimal reordering of the traditional IFSAR processing steps.
The requirement to efficiently form images over a large range of geometries has a profound impact on the design of a Synthetic Aperture Radar (SAR) system. This article shows how a data set conducive to efficient processing might increase the total RF bandwidth. It also presents examples of how a fixed RF bandwidth might then limit SAR geometries.
SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.
Lynx is a high resolution, synthetic aperture radar (SAR) that has been designed and built by Sandia National Laboratories in collaboration with General Atomics (GA). Although Lynx may be operated on a wide variety of manned and unmanned platforms, it is primarily intended to be fielded on unmanned aerial vehicles. In particular, it may be operated on the Predator, I-GNAT, or Prowler II platforms manufactured by GA Aeronautical Systems, Inc. The Lynx production weight is less than 120 lb. and has a slant range of 30 km (in 4 mm/hr rain). It has operator selectable resolution and is capable of 0.1 m resolution in spotlight mode and 0.3 m resolution in stripmap mode. In ground moving target indicator mode, the minimum detectable velocity is 6 knots with a minimum target cross-section of 10 dBsm. In coherent change detection mode, Lynx makes registered, complex image comparisons either of 0.1 m resolution (minimum) spotlight images or of 0.3 m resolution (minimum) strip images. The Lynx user interface features a view manager that allows it to pan and zoom like a video camera. Lynx was developed under corporate finding from GA and will be manufactured by GA for both military and commercial applications. The Lynx system architecture will be presented and some of its unique features will be described. Imagery at the finest resolutions in both spotlight and strip modes have been obtained and will also be presented.
This paper addresses theoretical aspects of forming images from an airborne Synthetic Aperture Radar (SAR) of targets buried below the earth's surface. Soil is generally a lossy, dispersive medium, with wide ranging variability in these attributes depending on soil type, moisture content, and a host of other physical properties. Focussing a SAR subsurface image presents new dimensions of complexity relative to its surface-image counterpart, even when the soil's properties are known. This paper treats the soil as a lossy, dispersive half space, and presents a practical model for the radar echo-delay time to point scatterers within it. This model is then used to illustrate effects of refraction, dispersion, and attenuation on a SAR's phase histories, and the resulting image. Various data collection geometries and processing strategies are examined for both 2-Dimensional and 3-Dimensional SAR images. The conclusions from this work are that 1) focussing a SAR image must generally take into account both refraction and dispersion, 2) resolving targets at different depths in lossy soils requires perhaps unprecedented sidelobe attenuation, that for some soils may only be achievable with specialized window functions, 3) the impulse response of the soil itself places a practical limit on the usable bandwidth of the radar, and 4) dynamic ranges and sensitivities will need to be orders of magnitude greater than typical surface-imaging SARs, leading to significant impact on SAR parameters, for example compressing the usable range of pulse repetition frequencies (PRFs).
Synthetic Aperture Radar (SAR) is used to form images that are maps of radar reflectivity of some scene of interest, from range soundings taken over some spatial aperture. Additionally, the range soundings are typically synthesized from a sampled frequency aperture. Efficient processing of the collected data necessitates using efficient digital signal processing techniques such as vector multiplies and fast implementations of the Discrete Fourier Transform. Inherent in image formation algorithms that use these is a trade-off between the size of the scene that can be acceptably imaged, and the resolution with which the image can be made. These limits arise from migration errors and spatially variant phase errors, and different algorithms mitigate these to varying degrees. Two fairly successful algorithms for airborne SARs are Polar Format processing, and Overlapped Subaperture (OSA) processing. This report introduces and summarizes the analysis of generalized Tiered Subaperture (TSA) techniques that are a superset of both Polar Format processing and OSA processing. It is shown how tiers of subapertures in both azimuth and range can effectively mitigate both migration errors and spatially variant phase errors to allow virtually arbitrary scene sizes, even in a dynamic motion environment.
Synthetic Aperture Radar (SAR) from an airborne platform has been proposed for imaging targets beneath the earth`s surface. The propagation of the radar`s energy within the ground, however, is much different than in the earth`s atmosphere. The result is signal refraction, echo delay, propagation losses, dispersion, and volumetric scattering. These all combine to make SAR image formation from an airborne platform much more challenging than a surface imaging counterpart. This report treats the ground as a lossy dispersive half-space, and presents a model for the radar echo based on measurable parameters. The model is then used to explore various imaging schemes, and image properties. Dynamic range is discussed, as is the impact of loss on dynamic range. Modified window functions are proposed to mitigate effects of sidelobes of shallow targets overwhelming deeper targets.