Fully-polarimetric X-band (9.6 GHz center frequency) VideoSAR with 0.125-meter ground resolution flew collections before, during, and after the fifth Source Physics Experiment (SPE-5) underground chemical explosion. We generate and exploit synthetic aperture RADAR (SAR) and VideoSAR products to characterize surface effects caused by the underground explosion. To our knowledge, this has never been done. Exploited VideoSAR products are "movies" of coherence maps, phase-difference maps, and magnitude imagery. These movies show two-dimensional, time-varying surface movement. However, objects located on the SPE pad created unwanted, vibrating signatures during the event which made registration and coherent processing more difficult. Nevertheless, there is evidence that dynamic changes are captured by VideoSAR during the event. VideoSAR provides a unique, coherent, time-varying measure of surface expression of an underground chemical explosion.

In past research, two-pass repeat-geometry synthetic aperture radar (SAR) coherent change detection (CCD) predominantly utilized the sample degree of coherence as a measure of the temporal change occurring between two complex-valued image collects. Previous coherence-based CCD approaches tend to show temporal change when there is none in areas of the image that have a low clutter-to-noise power ratio. Instead of employing the sample coherence magnitude as a change metric, in this paper, we derive a new maximum-likelihood (ML) temporal change estimate-the complex reflectance change detection (CRCD) metric to be used for SAR coherent temporal change detection. The new CRCD estimator is a surprisingly simple expression, easy to implement, and optimal in the ML sense. This new estimate produces improved results in the coherent pair collects that we have tested.

While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

This report describes the significant processing steps that were used to take the raw recorded digitized signals from the bistatic synthetic aperture RADAR (SAR) hardware built for the NCNS Bistatic SAR project to a final bistatic SAR image. In general, the process steps herein are applicable to bistatic SAR signals that include the direct-path signal and the reflected signal. The steps include preprocessing steps, data extraction to for a phase history, and finally, image format. Various plots and values will be shown at most steps to illustrate the processing for a bistatic COSMO SkyMed collection gathered on June 10, 2013 on Kirtland Air Force Base, New Mexico.

We have employed the Arecibo Observatory Planetary Radar (AO) transmitter and the Mini-RF radar onboard NASA's Lunar Reconnaissance Orbiter (LRO) as a receiver to collect bistatic data of the lunar surface. In this paper, we demonstrate the ability to form bistatic polarimetric imagery with spatial resolution on the order of 50m, and to create polarimetric maps that could potentially reveal the presence of ice in lunar permanently shadowed craters. We discuss the details of the signal processing techniques that are required to allow these products to be formed.

Beamforming is a methodology for collection-mode-independent SAR image formation. It is essentially equivalent to backprojection. The authors have in previous papers developed this idea and discussed the advantages and disadvantages of the approach to monostatic SAR image formation vis-a-vis the more standard and time-tested polar formatting algorithm (PFA). In this paper we show that beamforming for bistatic SAR imaging leads again to a very simple image formation algorithm that requires a minimal number of lines of code and that allows the image to be directly formed onto a three-dimensional surface model, thus automatically creating an orthorectified image. The same disadvantage of beamforming applied to monostatic SAR imaging applies to the bistatic case, however, in that the execution time for the beamforming algorithm is quite long compared to that of PFA. Fast versions of beamforming do exist to help alleviate this issue. Results of image reconstructions from phase history data are presented.

In recent papers the authors discussed the advantages of forming spotlight-mode SAR imagery from phase history data via a technique that is rooted in the principles of phased-array beamforming, which is closely related to back-projection. The application of a traditional autofocus algorithm, such as Phase Gradient Autofocus (PGA), requires some care in this situation. Specifically, a stated advantage of beamforming is that it easily allows for reconstruction of the SAR image onto an arbitrary imaging grid. One very useful grid, for example, is a Cartesian grid in the ground plane. Autofocus via PGA for such an image, however, cannot be performed in a straightforward manner, because in PGA a Fourier transform relationship is required between the image domain and the range-compressed phase history, and this is not the case for such an imaging grid. In this paper we propose a strategy for performing autofocus in this situation, and discuss its limitations. We demonstrate the algorithm on synthetic phase errors applied to real SAR imagery.

In this paper we describe an algorithm for fast spotlight-mode synthetic aperture radar (SAR) image formation that employs backprojection as the core, but is implemented such that its compute time is comparable to the often-used Polar Format Algorithm (PFA). (Standard backprojection is so much slower than PFA that it is impractical to use in many operational scenarios.) We demonstrate the feasibility of the algorithm on real SAR phase history data sets and show some advantages in the SAR image formed by this technique.

In this paper we show that the technique for spotlight-mode SAR image formation generally known as "backprojection" or "time-domain" is most easily derived and described in terms of the well-known methods of phased-array beamforming. By contrast, backprojection has been typically developed via analogy to tomographic imaging, which restricts this technique to the case of planar wavefronts. We demonstrate how the very simple notion of delay-and-sum beamforming leads directly to the backprojection algorithm for SAR, including the case for curved wavefronts. We further explain why backprojection offers a certain elegant simplicity for SAR imaging, and allows direct one-step computation of several useful SAR products, including an orthographically correct image free of any geometric or defocus effects from wavefront curvature and also free of the effects of terrain-elevation-induced defocus. (This product requires as an input a pre-existing digital elevation map (DEM) of the scene to be imaged.) In addition, we'll demonstrate why beamforming yields a mode-independent SAR image formation algorithm, i.e. one that can just as easily accommodate strip-map or spotlight-mode phase histories collected on an arbitrary flight path.

In this paper we describe a new method for creating three-dimensional images using pairs of synthetic aperture radar (SAR) images obtained from a unique collection geometry. This collection mode involves synthetic apertures that have a common centei: In this sense the illumination directions for the two SAR images are the same, while the slant planes are at different spatial orientations. The slant plane orientations give rise to cross-range layover (foreshortening) components in the two images that are of equal magnitude but opposite directions. This differential crossrange layover is therefore proportional to the elevation of a given target, which is completely analogous to the situation in stereo optical imaging, wherein two $lm planes (corresponding to the two slant planes) result in elevationdependent parallax. Because the two SAR collections are coherent in this particular collection mode, the images have the same speckle patterns throughout. As a result, the images may be placed into stereo correspondence via calculation of correlations between micro-patches of the complex image data. The resulting computed digital stereo elevation map can be quite accurate. Alternatively, an analog anaglyph can be displayed for 3-0 viewing, avoiding the necessity of the stereo correspondence calculation.

A new spotlight-mode synthetic aperture radar im- age formation approach is presented that directly utilizes the reflected electromagnetic returns collected on a polar grid. This approach eliminates polar-to-rectangular grid interpolation by employing chirp z-transforms in two dimensions. Since the chirp z-transform can be implemented via fast Fourier transforms (FFTs), this image formation algorithm consists almost entirely of FFTs allowing it to exploit computationally-efficient FFT engines for fast image formation speeds. This paper presents the algo- rithm, and compares the operation counts and execution time between the new algorithm and traditional polar formatting, which employs interpolation. The paper also presents conditions for which the chirp z-transform in two dimensions is advanta- geous.

While the chief cause of defocus in airborne spotlight-mode imagery is uncompensated errors in the measurement of the aircraft position as it traverses the synthetic aperture, another physical phenomenon can cause blurring in the formed SAR image as well. This is the injection of phase errors into the collected SAR phase history data by random fluctuations in the index of refraction as the microwave pulses propagate through an atmosphere that contains irregularities in the tropospheric water vapor distribution. In this paper, we show that in SAR imagery collected under certain conditions, these phase errors can be detected and corrected using a robust autofocus algorithm such as Phase Gradient Autofocus (PGA). The phase errors are confirmed as having been propagation-induced by demonstrating that they exhibit a power-law spectrum described by Tatarski, based on the turbulence model of Kolmogorov.

The polar format algorithm (PFA) is a computationally efficient image formation method for high-resolution spotlight-mode SAR data collections. Yet, its usual real-time implementation waits until the entire synthetic aperture has been collected before beginning image formation. This results in a latency time. This paper presents a new approach to PFA that performs range and azimuth interpolation and range compression as the aperture is collected. Thus, the remaining latency is approximately the azimuth compression time. Performing image formation during aperture collection makes minimum-latency PFA a viable real-time image formation algorithm.

SAR interferometry is a technique used to reconstruct detailed terrain height maps. The technique requires two SAR images of the same patch of ground. In order for the interferometric process to succeed, the imaging collection geometry must be within tightly held constraints. The two images are registered and the phases are compared using a 2-dimensional averaging box of several pixels. This phase difference is then proportional to the terrain height at the location of the center of the averaging box.This local averaging process is important because it reduces phase-noise and subsequently produces better height maps. The process, however, assumes that the phase difference is constant over the averaging box. In areas where steep slopes exist, this assumption is violated and the resulting phase difference measurements are in error, resulting in corrupted height maps.This paper presents a technique, which extends the model of the phase in the averaging box to allow a 2-dimensional linear phase slope to exist. The process estimates the constant phase (the phase that is a measure of the local terrain height) and the phase slope (which is a measure of the terrain slope) in an individual averaging box. Extending the model to include the linear phase slopes greatly improves the constant phase difference estimates, especially in areas of steep terrain. This results in much more accurate and reliable terrain products.This paper demonstrates the viability of the technique on actual SAR data.