Estimating the length of a radar shadow in shadow-feature-enhanced detection using a fuzzy system

Abstract

AbstmctShadow-feature-enhanced radar detection algorithms potentially allow the probability of target detection to be substantially increased when a target casts a radar shadow across a region of clutter beyond it. However, when the length of the radar shadow is not correctly known, much of the potential performance gain may be lost. We demonstrate a method for estimating the length of the radar shadow using a simple fuzzy system. We apply the shadow length estimation to the shadowfeature-enhanced MGCFAR detector, showing that its performance can be greatly improved when t h e shadow length is not known a priori.

Fuzzy statistical normalization CFAR detector for non-rayleigh data

“…However, the clutter here is caused by interfering targets, such as isolated rock outcrops, wrecks, and coral reefs, and is defined as the extended upper tail of the output distribution in the absence of a target signal [30]. The lower shadow area noise refers to the lower power noise and lower power reverberation in the region screened by an object [31]. When the data values are available, there is uncertainty about the exact category of the data.…”