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  1. Bistatic SAR: Imagery & Image Products.

    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-colormore » multi-view (2CMV) and coherent change detection (CCD) are presented.« less
  2. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

    In this paper, we derive a new optimal change metric to be used in synthetic aperture RADAR (SAR) coherent change detection (CCD). Previous CCD methods tend to produce false alarm states (showing change when there is none) in areas of the image that have a low clutter-to-noise power ratio (CNR). The new estimator does not suffer from this shortcoming. It is a surprisingly simple expression, easy to implement, and is optimal in the maximum-likelihood (ML) sense. The estimator produces very impressive results on the CCD collects that we have tested.
  3. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection.

    Abstract not provided.
  4. A New Maximum-Likelihood Change Estimator for Two-Pass SAR Coherent Change Detection

    Abstract not provided.
  5. Considerations for autofocus of spotlight-mode SAR imagery created using a beamforming algorithm.

    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 bemore » 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.« less
  6. Bistatic SAR: Proof of Concept.

    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 themore » 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.« less
  7. A beamforming algorithm for bistatic SAR image formation.

    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--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 disadvantagemore » 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.« less
  8. Comparison of polar formatting and back-projection algorithms for spotlight-mode SAR image formation.

    No abstract prepared.
  9. Correction of propagation-induced defocus effects in certain spotlight-mode SAR collections.

    No abstract prepared.

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