Sparse Signal Reconstruction And Its Application In Doa Estimation

Compressive sensing (CS) theory has attracted widespread attention in recent years. As the topic of sparse signal reconstruction has evolved very rapidly in the last decade, some improved methods based on it have emerged, which can provide even better performance. At present, the common sparse reconstruction algorithm mainly includes basis pursuit (BP) algorithm and orthogonal matching pursuit (OMP) algorithm. Sparse reconstruction is used in many fields such as coding theory, medicine, astronomy and geophysics.In this thesis, the CS theory is applied to DOA estimation of target, and from the perspective of sparse vector reconstruction to realize the signal DOA estimation, and the problem could be solved by CS method. The main works in this thesis is organized as follows:(1) The related background knowledge of algorithm in this paper and the main theory of Compressive Sensing are introduced.(2) Traditional OMP algorithm is susceptible to the affection of inter-atom interference of redundant dictionary which leads to unsatisfactory reconstruction effect. According to this problem, we proposed a fast method for DOA estimation of coherent signal from a sparse signal reconstruction perspective, which is based on OMP algorithm of adaptive mitigate inter-atom interference (AMIAI-OMP). First we design an adaptive sensing dictionary to mitigate affection of inter-atom interference of redundant dictionary. And then estimate the DOA of coherent signal based on OMP algorithm. The method with AMIAI-OMP algorithm is much faster than the method based on BP algorithm. Moreover, it can resolve more signals than the array sensors.(3) According to the structure features of minimum redundancy linear array (MRLA) that is obtaining larger antenna aperture through a smaller number of array sensors, MRLA is applied into l1-SVD method to estimate signal DOAs based on the structure features. Simulations demonstrate that the proposed approach is effective and compare to l1-SVDmethod it could estimate more DOA of signal source, and it is capable of estimating more DOAs with fewer antenna elements.