Research On Radar Constant False Alarm Rate Detection Algorithm Based On Compressed Sensing

Constant false alarm rate(CFAR)detection technology is an important part of radar target automatic detection,and it is one of the research hotspots in the field of modern radar signal processing.Compressed sensing theory can effectively solve the problem of large data volume in radar target detection processing,and it is widely used.Therefore,this paper based on the theory of Compressed Sensing(CS),combines the variable identification(Vl)-CFAR detection algorithm to study the radar target signal detection algorithm.First,the paper describes the detection principle of CFAR and CS theory.The Vl-CFAR detection algorithm is simulated and compared,and the advantages of the mean class CFAR are gathered by VI-CFAR to carry out subsequent research and improvement.The CS theory is discussed from three aspects:signal sparsity,measurement matrix selection and reconstruction algorithnim which provides a theoretical basis for the improved algorithm.Secondly,the target detection algorithm based on compressed sensing is studied.The binary detection model under the theory of compressed sensing is constructed by using the characteristics that the radar signal can be sparsely represented.The sparse dictionary base is constructed by using the transmitted signals with different delays.The unreconstructed CSCA-CFAR algorithm with unit average(CA)-CFAR as detector is analyzed.Aiming at the problem of detecting performance degradation in a non-uniform environment,a CSVI-CFAR algorithm is proposed,it is verified that the detection performance of this algorithm is good in the simulation environment.Finally,the constant false alarm rate detection algorithm based on reconstruction is studied.The existing complex approximation message passing(CAMP)algorithm and its optimal threshold adaptive method are studied,and the CAMP detection algorithm which restores the sparse estimation value to zero as the decision criterion is analyzed.For the problem that the existing CAMPCA-CFAR algorithm has performance degradation when there has interference target,this paper uses the CAMP algorithm can recover the non-sparse estimation characteristics of signals and proposes a CAMPVI-CFAR detection algorithm and validates the effectiveness of the CAMPVI-CFAR algorithm in simulation environment.