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.
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.
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.
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.
We generally desire to relate radar data values to the Radar Cross Section (RCS) of a radar target echo. This is essential to selecting proper gain values in a radar receiver, maintaining dynamic range, and to properly interpret the resulting data and data products. Ultimately, this impacts proper radar design. We offer herein a basic analysis of relevant concepts and calculations to properly calibrate a monostatic radar's echoes with respect to RCS, and to select appropriate receiver gain values.
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.
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.
Conventional signal processing to estimate radar Doppler frequency often assumes uniform pulse/sample spacing. This is typically more for the convenience of the 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.
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.