Abstract
We present normalizer design considerations for detection of targets in a high-clutter environment. Several classes of constant-false-alarm-rate (CFAR) normalizers have conventionally been used to bring out a target signal from the background noise and reverberation in active sonar signal processing. The special challenges of detection in high-clutter environments are outlined, and the normalizer classes are compared for their suitability of use in these environments. We consider statistical and multiple-look normalizers and give emphasis to the class of split-window mean-power normalizers and implementations that preserve target signal-to-noise ratio (SNR) and highlight structure while mitigating artifacts that are sometimes produced near clutter edges. Statistical comparisons and specific examples are presented, and we propose an efficient CFAR normalizer for high performance in regions of high clutter.
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