Performance of Automatic Target Recognition (ATR) algorithms for Synthetic Aperture Radar (SAR) systems relies
heavily on the system performance and specifications of the SAR sensor. A representative multi-stage SAR ATR
algorithm [1, 2] is analyzed across imagery containing phase errors in the down-range direction induced during the
transmission of the radar's waveform. The degradation induced on the SAR imagery by the phase errors is
measured in terms of peak phase error, Root-Mean-Square (RMS) phase error, and multiplicative noise. The ATR
algorithm consists of three stages: a two-parameter CFAR, a discrimination stage to reduce false alarms, and a
classification stage to identify targets in the scene. The end-to-end performance of the ATR algorithm is quantified
as a function of the multiplicative noise present in the SAR imagery through Receiver Operating Characteristic
(ROC) curves. Results indicate that the performance of the ATR algorithm presented is robust over a 3dB change in
multiplicative noise.
Template-based classification algorithms used with synthetic aperture radar (SAR) automatic target recognition (ATR)
degrade in performance when used with spatially mismatched imagery. The degradation, caused by a spatial mismatch
between the template and image, is analyzed to show acceptable tolerances for SAR systems. The mismatch between
the image and template is achieved by resampling the test imagery to different pixel spacings. A consistent SAR dataset
is used to examine pixel spacings between 0.1069 and 0.2539 meters with a nominal spacing of 0.2021 meters.
Performance degradation is observed as the pixel spacing is adjusted, Small amounts of variation in the pixel spacing
cause little change in performance and allow design engineers to set reliable tolerances. Alternatively, the results show
that using templates and images collected from slightly different sensor platforms is a very real possibility with the
ability to predict the classification performance.
A multi-stage Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) system is analyzed across images
of various pixel areas achieved by both square and non-square resolution. Non-square resolution offers the ability to
achieve finer resolution in the range or cross-range direction with a corresponding degradation of resolution in the cross-range
or range direction, respectively. The algorithms examined include a standard 2-parameter Constant False Alarm
Rate (CFAR) detection stage, a discrimination stage, and a template-based classification stage. Performance for each
stage with respect to both pixel area and square versus non-square resolution is shown via cascaded Receiver Operating
Characteristic (ROC) curves. The results indicate that, for fixed pixel areas, non-square resolution imagery can achieve
statistically similar performance to square pixel resolution imagery in a multi-stage SAR ATR system.
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