Fluctuating target detection in presence of non Gaussian clutter in OFDM radars
Today, Orthogonal Frequency Division Multiplexing (OFDM) radars are very interested in detection of low Radar Cross Section (RCS) targets. A vast number of research work has been reported about target detection in OFDM radars. But all these papers concern detection in presence of Gaussian interference and also assume that target has a constant scattering coefficient or RCS. In this paper, we present a Generalized Likelihood Ratio (GLR) detector for detecting a moving target in presence of Gaussian interference and evaluate its performance in presence of different types of clutter distribution and target fluctuation. We assume three scenarios for detecting a fluctuating target in the presence of four different distributions of clutter; Rayleigh, Log-normal, Weibull and K-compound. In the first scenario, we consider the RCS's of target are constant subcarrier to subcarrier and pulse to pulse in a burst of pulses while they are varying fast according to Chi-square probability density function (swerling case II) burst to burst. In the second scenario, we assume that the RCS of target varies slowly according to Chi-square probability density function (swerling case I) subcarrier to subcarrier and they are constant pulse to pulse in a burst of pulses while they are varing fast according to Chi-square probability density function burst to burst. And in the third scenario, we assume the scattering coefficients of target are varing fast subcarrier to subcarrier and burst to burst, while they are constant pulse to pulse in a burst of pulses. We provide a few numerical examples to illustrate the detection performance of moving target under conditions of three scenarios, fluctuating models and different distributions of clutter and demonstrate the achieved performance improvement due to the OFDM signaling.
fluctuation detection clutter ofdm radar generalized likelihood ratio test