Research on DOA Estimation Algorithm Based on Sparse Spatial Fusion

• 1、Department of Information Science and Engineering, Hunan University, Changsha 410082

Abstract：The note on the theory of using the compressed sensing theory to estimate the angle of arrival of the array signal in the intelligent vehicle system based on radar-communication is the spatial sparse partitioning and the optimization of the sparse reconstruction algorithm. Different partitioning methods will result in different array flow patterns, and the construction of array flow patterns is the basis of algorithm estimation. At present, the establishment of the sparse model is simply based on the equal angle or the equal sinusoidal division method. However, in the normal and end-fire directions, the orthogonality of the two is different, and the estimation results are also different. To this end, this paper designs a spatial sparse partitioning model combining the equal sinusoidal and the equal angle division. The simulation shows that this model has certain advantages compared with the traditional division method. In addition, in order to optimize the performance of the SAMP algorithm in integrated systems, this paper proposes an improved matching tracking algorithm. Based on the SAMP algorithm, this algorithm sets strict comparison of residual values as termination conditions, and automatically adjusts the number of atoms in the candidate set through an adaptive process to achieve accurate signal reconstruction. The theoretical derivation and experimental simulations show that this algorithm has obvious benifits in terms of operation speed and reconstruction accuracy while maintaining the advantages of this original algorithm.

keywords： wireless communication technology radar communication Intergration compressed sensing(CS) spatial sparse Partitioning optimized reconstruction algorithm

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