Signal Detection Under The Interference Background

In the field of signal processing,Array signal processing plays a very important role.With the continuous development of array signal processing and tracking and weak target signal parameters estimation method research is unceasingly thorough,the spatial spectrum estimation,namely the DOA(Direction of DOA,concatenated)estimation has become an important research Direction,and the radar,sonar,radio astronomy,and wireless communications and other fields of national defense and civil has important application value.In the actual signal work environment,however,because of the source of the clutter signal is complex,weak target signals are often submerged in strong interference and the strong background noise,thus seriously inhibit the performance of the conventional spatial spectrum estimation method.Based on the conventional spatial spectrum estimation method under the background of strong interference performance severely affected question has carried on the thorough research,the main work content can be summarized as follows:1.Induction and analysis of the conventional spatial spectrum estimation method,and the classic Bartlett of spatial spectrum estimation algorithm,Minimum variance distortionless response(MVDR,Minimum variance distortionless response)algorithm and multiple signal classification(MUSIC,multiple signal classification)algorithm has carried on the simulation results under different conditions and the performance comparison between different algorithms.2.Research the two kinds of suitable for strong interference under the background of spatial spectrum estimation methods:orthogonal projection transformation method and the expansion of the noise subspace method.(1)in the method of orthogonal projection transformation,assuming that strong interference to wave direction of prior information known in advance.In this context,through solving the interference signal steering vector Zhang Chengzi orthogonal projection of the space,can be directly received snapshot data pretreatment of samples,the projection into the vertical interference signal subspace,so as to eliminate the influence of strong interference.At the same time,inhibiting factor is defined and avoid the process of orthogonal projection for the effect of a weak signal.After the elimination of interference signal component,classic spatial spectral estimation performance will not be significantly suppressed.(2)extending the noise subspace method,its basic idea is by putting a strong interference r.vishny by oriented vector signal subspace incorporated into the original wave signal to noise subspace,the broadening of the noise subspace,to eliminate interference effects on the target signal.Finally,by the conventional spatial spectrum estimation methods,such as MUSIC algorithm can estimate to the information of the target signal DOA.This article on these two methods respectively and results analysis,the simulation experiment compares the arrays in the different number of interference and number,weak signals from different perspectives,different arrays and amplitude-phase error cases,the performance of the two methods.Experimental results show that the two methods are to be able to get a good DOA estimation of weak signal submerged by strong interference problem.Moderate,orthogonal projection transformation method and computational complexity but need to know the priori information of strong interference signal,and extending the noise subspace method need not predict the priori information of the strong interference,a wider range of application.3.The analysis of the broadband Signal under the background of non-coherent subspace processing Method of spatial spectrum estimation(ISM,Incoherent Signal-subspace Method),and combined with the above two methods,the successful promotion of broadband Signal DOA estimation under the strong interference in solving the problems.This paper presents a detailed derivation of non-coherent subspace processing method to carry on the simulation results under different conditions and performance analysis.