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 di fficult to achieve, and is limite d 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. Thes e can often be much more accurate than what might be achievable by the radar itself. Cons equently, SAR images may be aligned to some higher accuracy database, there by improving the geolocation of features in the SAR image. Examples offer anecdotal evidence of the viability of such an approach. - 4 - Acknowledgements This report is the result of an unf unded Research and Development effort. A special thank you to Tommy Burks for his da ta collections in the Albuquerque area.
This document contains the final report for the midyear LDRD titled "Extension of Interferometric Synthetic Aperture Radar to Multiple Phase-Centers." This report presents an overview of several methods for approaching the two-target in layover problem that exists in interferometric synthetic aperture radar systems. Simulation results for one of the methods are presented. In addition, a new direct approach is introduced.
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.
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.
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.
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.
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.
An important part of a navigation system for a moving platform is the estimation of the rate of travel. This document presents a method for estimating the platform velocity in 3-dimensions using multiple antenna subarrays which could be used to augment navigation in a GPS-degraded environment. An advantage of this technique is that it does not require any knowledge of a positions of any landmarks. Results from radar data collected by the Sandia National Laboratories demonstration radar system are presented to illustrate the promise of this technique.
In comparing system performance for ground moving target indicator (GMTI) radar systems, various metrics are used. It is highly desirable that the metric be simple and powerful. Ideally it is a single number, or a plot. It is often the case that a single number is not sufficient to describe the radar performance under all operational conditions. In spite of this, it is still common to attempt to use a simple metric, such as the minimum detectable velocity (MDV). This paper discusses the concept of minimum detectable velocity with the goal of showing what this metric attempts to communicate, and what may not be properly communicated by this metric without careful attention. Basic parameters that affect the minimum detectable velocity are presented.
Various parameters can affect the ground moving target indicator (GMTI) radar performance. One such parameter that may often be overlooked is that of the unintended polarization of the antenna, e.g., the cross-polarization response. This paper discusses the issue of cross-polarization on clutter attenuation performance for GMTI radars.
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.
Radar receivers with multiple receive channels generally strive to make the receive channels as ideal as possible, and as alike as possible. This is done via prudent hardware design, and system calibration. Towards that end, we require a quality metric for ascertaining the goodness of a radar channel, and its match to sibling channels. We propose a relevant and useable metric to do just that.
Many types of dark regions occur naturally or artificially in Synthetic Aperture Radar (SAR) and Coherent Change Detection (CCD) products. Occluded regions in SAR imagery, known as shadows, are created when incident radar energy is obstructed by a target with height from illuminating resolution cells immediately behind the target in the ground plane. No return areas are also created from objects or terrain that produce little scattering in the direction of the receiver, such as still water or flat plates for monostatic systems. Depending on the size of the dark region, additive and multiplicative noise levels are commonly measured for SAR performance testing. However, techniques for radar performance testing of CCD using dark regions are not common in the literature. While dark regions in SAR imagery also produce dark regions in CCD products, additional dark regions in CCD may further arise from decorrelation of bright regions in SAR imagery due to clutter or terrain that has poor wide-sense stationarity (such as foliage in wind), man-made disturbances of the scene, or unintended artifacts introduced by the radar and image processing. By comparing dark regions in CCD imagery over multiple passes, one can identify unintended decorrelation introduced by poor radar performance rather than phenomenology. This paper addresses select dark region automated measurement techniques for the evaluation of radar performance during SAR and CCD field testing.
We desire a metric with which to evaluate the "goodness" of various image compression schemes in recreating an original Synthetic Aperture Radar image. Herein we propose a "coherence" measure that results in a single quality number for such an evaluation.
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.
Antenna apertures are often parsed into subapertures for Direction of Arrival (DOA) measurements. However, when the overall aperture is tapered for sidelobe control, the locations of phase centers for the individual subapertures are shifted due to the local taper of individual subapertures. Furthermore, individual subaperture gains are also affected. These non-uniform perturbations complicate DOA calculations. Techniques are presented to calculate subaperture phase center locations, and algorithms are given for equalizing subapertures' gains.
This document discusses some interesting features of the new coherence estimator in [1] . The estimator is d erived from a slightly different viewpoint. We discuss a few properties of the estimator, including presenting the probability density function of the denominator of the new estimator , which is a new feature of this estimator . Finally, we present an appr oximate equation for analysis of the sensitivity of the estimator to the knowledge of the noise value. ACKNOWLEDGEMENTS The preparation of this report is the result of an unfunded research and development activity. 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 Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000.
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.
It is commonly observed that resolution plays a role in coherent change detection. Although this is the case, the relationship of the resolution in coherent change detection is not yet defined . In this document, we present an analytical method of evaluating this relationship using detection theory. Specifically we examine the effect of resolution on receiver operating characteristic curves for coherent change detection.
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. Acknowledgements The preparation of this report is the result of an unfunded research and development activity. 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 Energy's National Nuclear Security Administ ration under contract DE-AC04-94AL85000.
The complex coherence function describes information that is necessary to create maps from interferometric synthetic aperture radar (InSAR). This coherence function is complicated by building layover. This paper presents a mathematical model for this complex coherence in the presence of building layover and shows how it can describe intriguing phenomena observed in real interferometric SAR data.
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.
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 coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.
Monopulse radar is a well-established technique for extracting accurate target location information in the presence of target scintillation. It relies on the comparison of at least two patterns being received simultaneously by the antenna. These two patterns are designed to differ in the direction in which we wish to obtain the target angle information. The two patterns are compared to each other through a standard method, typically by forming the ratio of the difference of the patterns to the sum of the patterns. The key to accurate angle information using monopulse is that the mapping function from the target angle to this ratio is well-behaved and well-known. Errors in the amplitude and phase of the signals prior and subsequent to the comparison operation affect the mapping function. The purpose of this report is to provide some intuition into these error effects upon the mapping function.
This document is the final report for the 2009 Antarctica Crevasse Detection Radar (CDR) Project. This portion of the project is referred to internally as Phase 2. This is a follow on to the work done in Phase 1 reported on in [1]. Phase 2 involved the modification of a Sandia National Laboratories MiniSAR system used in Phase 1 to work with an LC-130 aircraft that operated in Antarctica in October through November of 2009. Experiments from the 2006 flights were repeated, as well as a couple new flight tests to examine the effect of colder snow and ice on the radar signatures of 'deep field' sites. This document includes discussion of the hardware development, system capabilities, and results from data collections in Antarctica during the fall of 2009.
This document is the final report for the Antarctica Synthetic Aperture Radar (SAR) Project. The project involved the modification of a Sandia National Laboratories MiniSAR system to operate at X-band in order to assess the feasibility of an airborne radar to detect crevasses in Antarctica. This radar successfully detected known crevasses at various geometries. The best results were obtained for synthetic aperture radar resolutions of at most one foot and finer. In addition to the main goal of detecting crevasses, the radar was used to assess conops for a future operational radar. The radar scanned large areas to identify potential safe landing zones. In addition, the radar was used to investigate looking at objects on the surface and below the surface of the ice. This document includes discussion of the hardware development, system capabilities, and results from data collections in Antarctica.
We present new methods for resolving IFSAR ambiguities and SAR layover. The analytic properties of these techniques make them well suited for reliable, efficient computation.
The Rapid Terrain Visualization interferometric synthetic aperture radar was designed and built at Sandia National Laboratories as part of an Advanced Concept Technology Demonstration (ACTD) to "demonstrate the technologies and infrastructure to meet the Army requirement for rapid generation of digital topographic data to support emerging crisis or contingencies". This sensor is currently being operated by Sandia National Laboratories for the Joint Precision Strike Demonstration (JPSD) Project Office to provide highly accurate digital elevation models (DEMs) for military and civilian customers, both inside and outside of the United States. The sensor achieves better than DTED Level IV position accuracy in near real-time. The system is being flown on a deHavilland DHC-7 Army aircraft. This paper outlines some of the technologies used in the design of the system, discusses the performance, and will discuss operational issues. In addition, we will show results from recent flight tests, including high accuracy maps taken of the San Diego area.
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.
Interferometric synthetic aperture radar (IFSAR) extends the two-dimensional imaging capability of traditional synthetic aperture radar to three-dimensions by using an aperture in the elevation plane to estimate the 3-D structure of the target. The operation of this additional aperture can be viewed from a null-steering point of view rather than the traditional phase determination point of view. Knowing that IFSAR can be viewed from the null-steering perspective allows us to take advantage of the mathematical foundation developed for null-steering arrays. In addition, in some problems of interest in IFSAR the null-steering perspective provides better intuition and suggests alternative solutions. One example is the problem of estimating building height where layover is present.
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.