Abstract
Imaging sonar systems including forward looking sonars, synthetic aperture sonars, and real aperture sonars produce large quantities of data and are often connected to automated target recognition (ATR) algorithms. Performance of these algorithms degrades, sometimes significantly, with changes in environmental reverberation, seafloor sediment characteristics, and target characteristics. However, most ATR algorithms have no capability to assess their own performance, flag data that is invalid, or convey when their results should not be trusted or utilized by humans or autonomous algorithms. Performance estimation algorithms can be used in conjunction with ATR to supplement these shortcomings. Estimates of signal-to-noise ratio, image contrast, and resolution can be used to assess deviation from nominal performance capabilities, while regressing ATR performance against imagery characteristics or other through-the-sensor metrics can be used to estimate false alarm rate.
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