Sidelobes Of Targets Research Articles

Modified Adaptive Pulse Compression Algorithm for Targets With Range-Straddling

Adaptive pulse compression (APC) has been proposed based on the minimum mean square error (MMSE) criterion to effectively suppress range sidelobes of strong targets and retrieve all targets in multi-target scenarios. However, MMSE-based algorithms suffer from deteriorated performance in the presence of targets with range-straddling due to modelling mismatch. This degradation can be partially compensated by modified MMSE-based algorithms. To further suppress sidelobes when range straddling occurs, we propose a modified APC algorithm robust to targets with range-straddling, namely range-straddling-robust APC (RSR-APC). We first establish the signal model for targets with range-straddling and then derive the expressions of the MMSE filter based on matched filter outputs and the range-straddling offsets based on an improved Rife algorithm. Simulation results show that the proposed algorithm can suppress sidelobes of targets with range-straddling and improve estimation accuracy of target positions in different scenarios.

Sparse Representation for Target Parameter Estimation in CDR-Based Passive Radar

In the China digital radio (CDR)-based passive radar, when the range-Doppler (RD) map is generated by the classical matched filtering method, the target range profile has the mainlobe splitting phenomenon. To solve this problem, we first derive the reason for the target mainlobe splitting from the subcarrier domain. Then, we develop an effective-subcarrier-based complex fast sparse Bayesian learning (ES-CFSBL) algorithm to generate RD map. Finally, simulation and experimental results show that the developed algorithm can effectively reduce sidelobe level and make it easier to detect and track weak targets covered by strong target sidelobes. Besides, the proposed method can realize fractional delay estimation conveniently.