Research on sequential detection of adjacent multi-targets based on sparse channel estimation

High sidelobe peaks of auto-correlation function in the matching filter output incur interference to the detection of other adjacent targets.To achieve adjacent targets detection,sparse reconstruction theory was employed to obtain targets' position estimation.In the scenario with high SNR(signal to noise ratio),estimated results can be used directly for targets' detection;otherwise,i.e.in the scenario with low SNR,two detection algorithms are proposed.The first one,similar to CLEAN algorithm,utilizes the energy changes of matching filter output to determine the presence of targets,while the second one,considering the feature of auto-correlation function,combines main lobe change calculation and Page-test sequential detector to achieve multi-targets detection.Simulation and experimental data processing results demonstrate that the second algorithm achieved better weak targets' detection performance.