Experimental analysis of various estimators for target range estimation in high resolution radars

Abstract

The author analyses the target range estimation errors in pulse compression high-resolution radars (HRRs). Conventional radar signal processors assume a point target model in matched filtering-based detection and tracking. The author demonstrates through simulations that the performance degradation, under the point target assumption, can be significant for HRRs, where targets extend across several detection cells. Also, the author models events of backscatters from illuminated target and clutter as a non-homogenous Poisson process (NHPP). The corresponding maximum likelihood, maximum a posteriori, minimum mean square error and minimum mean absolute error estimators are derived for range estimation. Typical target detection process has been simulated and the performance of NHPP-based estimators has been compared to that of the most commonly used peak estimators, namely, the maximum point and interpolation peak estimators. Simulation results show that the proposed estimators significantly reduce target range estimation errors in HRRs.