Radar Transceiver Design for Extended Targets Based on Optimal Linear Detector

Abstract

This article considers the radar transceiver design problem for extended targets, aiming at improving the detection performance of radar systems. To circumvent the complicated Neyman–Pearson (NP) detector, we adopt the detector with linear structure. By analyzing its detection performance, we construct the transceiver design criterion. Based on this criterion, the waveform-filter design is formulated as a highly nonconvex fractional programming problem with constant modulus constraints (CMC) on the waveform. To tackle the formulated problem, we develop a block successive upper-bound minimization (BSUM) framework-based algorithm, in which the transceiver optimization variables are divided into blocks. It is shown that the divided blocks can be updated in a closed form at each iteration without the help of external optimization toolbox. The convergence of the proposed algorithm is proved theoretically. Numerical experiments validate the effectiveness of the proposed algorithm. Results highlight that the proposed criterion achieves comparable performance to the State-of-the-Art criteria on the NP detector, but outperforms its counterparts on the linear detector.