Fast Sidelobe Suppression for RFPA Signals via Windowed IAA with Dominant Components Selection

Random frequency and pulse repetition interval agile (RFPA) signals are known for their excellent anti-jamming and low probability of intercept performance. However, the matched filter (MF) outputs of such signals have high range-Doppler sidelobes, resulting in substantial degradation of the detection performance of weak targets located near strong targets or clutter. Iterative adaptive approaches (IAA) based on MF outputs have excellent capability of sidelobe suppression but with high computational burden, making them difficult for practical applications. In order to suppress range-Doppler sidelobes efficiently, a windowed IAA based on MF outputs with dominant components selection (WMF-SIAA) is proposed by considering the target sparsity. In this method, range-Doppler MF outputs within a cross-shaped processing window are taken as the inputs of the designed iterative adaptive filter and the dominant components of covariance matrix used in the iterative processing are selected for the calculation of complex amplitudes of targets based on the fact that the target number is far less than the total number of range-Doppler cells involved in the calculation of the covariance matrix, which can substantially decrease computational costs while achieving satisfactory sidelobe suppression performance. Simulation results demonstrate that WMF-SIAA can effectively suppress sidelobes of neighboring range-Doppler cells with low computational complexity and accurately estimate weak targets in complex scenarios containing multiple targets and ground clutter.