Analysis of Cell-Averaging based detectors for x 2 fluctuating targets in multitarget environments
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The x 2 family of signal fluctuation distributions represents the main fluctuation models which most radar targets follow it in their reflections. This family can be categorized as fluctuation distribution with two degrees of freedom and those with four degrees of freedom. The first category represents an important class of fluctuation models which when illuminated by a coherent pulse train, return a train of fully correlated pulses (Swerling I model) or fully decorrelated pulses (Swerling II model). The detection of this type of fluctuating targets is therefore of great importance. This paper is devoted to the analysis of Cell-Averaging (CA) based detectors for the case where the radar receiver noncoherently integrates M square-law detected pulses and the signal fluctuation obeys x 2 statistics with two degrees of freedom. These detectors include the Mean-Of (MO), the Greatest-Of (GO) and the Smallest-Of (SO) schemes. In these processors, the estimation of the noise power levels from the leading and the trailing reference windows is based on the CA technique. Exact formulas for the detection probabilities are derived, in the absence as well as in the presence of spurious targets. The primary and the secondary interfering targets are assumed to be fluctuating in accordance with the x 2 fluctuation model with two degrees of freedom (SWI & SWII). The numerical results show that the MO version has the best homogeneous performance, the SO scheme has the best multiple-target performance, while the GO procedure does not offer any merits, neither in the absence nor in the presence of outlying targets.
Key wordsAdaptive detectors Cell-averaging processors Noncoherent integration x2 fluctuating targets Target multiplicity environments
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