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  1. In previous 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 estimatormore » is a surprisingly simple expression, easy to implement, and optimal in the ML sense. As a result, this new estimate produces improved results in the coherent pair collects that we have tested.« less
  2. Useful products generated from interferometric synthetic aperture radar (IFSAR) complex data include height measurement, coherent change detection, and classification. The IFSAR coherence is a spatial measure of complex correlation between two collects, a product of IFSAR signal processing. A tacit assumption in such IFSAR signal processing is that one height target exists in each range-Doppler cell. This paper presents simulations of IFSAR coherence if two targets with different heights exist in a given range-Doppler cell, a condition in IFSAR collections produced by layover. It also includes airborne IFSAR data confirming the simulation results. The paper concludes by exploring the implicationsmore » of the results on IFSAR classification and height measurements.« less
  3. Spatially Interpolated Nonlinear Anodization in Synthetic Aperture Original formulation of spatially variant anodization for complex synthetic aperture radar (SAR) imagery oversampled at twice the Nyquist rate (2.OX). Here we report a spatially interpolating, noninteger-oversampled SVA sidelobe. The pixel's apparent IPR location is assessed by comparing its value to the sum of its value plus weighted comparable for exact interpolation. However, exact interpolation implies an ideal sine interpolator3 and large components may not be necessary. Note that P is the summation of IPR diagonal values. The value of a sine IPR on the diagonals is a sine-squared; values much less thanmore » cardinal direction (m, n) values. This implies that cardinal direction interpolation requires higher precision than diagonal interpolation. Consequently, we employed a smaller set. The spatially interpolated SVA used an 8-point/4-point sine interpolator described above. Table 1 shows the Table 1 results show a two-times speed-up using the 1.3x oversampled and spatially interpolated SVA over the Figure 1d. Detected results of 1.3x oversampled sine interpolated spatially variant« less
  4. A phase gradient autofocus system for use in synthetic aperture imaging accurately compensates for arbitrary phase errors in each imaged frame by locating highlighted areas and determining the phase disturbance or image spread associated with each of these highlight areas. An estimate of the image spread for each highlighted area in a line in the case of one dimensional processing or in a sector, in the case of two-dimensional processing, is determined. The phase error is determined using phase gradient processing. The phase error is then removed from the uncorrected image and the process is iteratively performed to substantially eliminatemore » phase errors which can degrade the image.« less

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