Research On Dynamic Direction Of Arrival Estimation Technology Based On Subarray Division

Direction of arrival(DOA)estimation is an important branch of array signal processing.With the development of electronic technology,algorithms in this field are developing towards the direction of high model complexity and strong computational nonlinearity.On the other hand,with the advancement of integration technology,the research of large-scale antenna array is facing a series of problems,such as engineering implementation difficulties,signal processing complexity and so on.In engineering practice,there are a large number of dynamic targets whose position information changes with time.How to track dynamic targets based on DOA estimation methods on large arrays has become a difficult point in research.Based on this background,this article will improve the subspace fitting algorithm with accurate angle estimation but high computational complexity,and realize the dynamic target direction of arrival estimation at the element level and the sub-array level respectively.The research is mainly divided into two parts:Firstly,an array element-level dynamic DOA estimation method is proposed.The current general process of dynamic direction of arrival estimation is to update the data covariance matrix or signal(noise)subspace using subspace iteration and update algorithms,and then perform direction of arrival estimation and tracking.First of all,the commonly used PAST-MUSIC algorithm is analyzed and simulated.Aiming at the low tracking accuracy of the algorithm,two improvements are made.First,the Rank-1 subspace update formula is used to replace the pass algorithm to update the data covariance matrix to improve the stability of the algorithm.Second,the subspace fitting algorithm is used to replace the music algorithm to improve the dynamic direction finding accuracy.Simulation results show that the algorithm is effective,but the amount of calculation is large.Therefore,the particle swarm algorithm is used to simplify the calculation process of the subspace fitting algorithm by gradually locking and narrowing the search range.The proposed PSO-SF algorithm can achieve stable and accurate estimation of the direction of arrival of dynamic targets at the element level,and can directly deal with relevant sources.Secondly,a sub-array-level dynamic DOA estimation method is proposed.When the number of array elements is large,the array element-level dynamic direction of arrival estimation algorithm is used with large data volume and complicated process.In order to reduce the computational complexity,consider combining the received data of several array elements into one sub-array data for direction of arrival estimation.Therefore,it is necessary to divide the sub-array first.This paper uses a sub-array division method based on the exhaustive method.The conversion matrix is constructed according to the divided sub-array structure,and the element-level data is converted into sub-array-level data.Then PSO-ML and PSO-SF two array element-level dynamic direction of arrival estimation methods are extended to the sub-array level,the angle estimation formulas of the sub-array-level maximum likelihood algorithm and the sub-array-level subspace fitting algorithm are derived.Simulation results show that the algorithm is effective,but the stability of B-PSO-ML algorithm is not strong and the effect of processing coherent sources is poor.This is caused by the rapid loss of population diversity and insufficient local search ability in the iterative process of the PSO algorithm.The CSO algorithm with a division of labor strategy is used for improvement.The improved B-CSO-ML algorithm can directly process coherent sources,has higher stability and smaller estimation errors,and can realize dynamic target DOA estimation at the sub-array level.