阵列元素交互作用下基于稀疏贝叶斯学习的离网DOA估计

Here， aiming at the problem of interaction among hydrophone array elements of actual sonar array causing estimation performance droppingof the array ' s direction of arrival ( DOA)，a DOA estimation method under uncertain interaction of array elementswas proposed. Firstly, based on the sparse Bayesian learning ( SBL) model, a spatial domain was discretized into a uniform grid, and the off-grid error was introduced. For interactionamong array elements, the interaction coefficient vector was introduced. Secondly, prior distributions of off-grid error and interaction coefficient vector were determined. Finally, the expectation maximization algorithm of Bayesian learning was used to iteratively update unknown parameters，and obtain the target space spectrum. Simulation results showed that the proposed method can have higher estimation accuracy and stronger multi-target resolving ability under larger unknown interaction of array elements.