基于OMP算法的极化敏感阵列多参数估计

Multi-Parameter Estimation for Polarization Sensitive Array Using Adaptive-OMP Algorithm

基于压缩感知的DOA估计方法在小快拍数下性能优越,并且具有天然的解相干能力,但在极化敏感阵列中运用很少。基于极化敏感阵列研究一种改进的OMP算法,能够成功估计出空域和极化域参数。该算法首先将极化敏感阵列信号接收矩阵重新建模,随后采用所提的改进OMP算法得到空域到达角估计结果。然后将求解出来的空域到达角代入到根据模值约束条件构造出来的代价函数中,通过闭合式解得到极化参数估计,从而实现了自动配对的空域和极化域的参数估计。仿真结果表明,该方法无论信号相干与否都能够得到良好的估计结果,并且在非相干情况下,估计性能总体优于极化ESPRIT算法及模值约束MUSIC算法。

The DOA estimation algorithm based on compressive sensing has superior performance in small snapshot and the natural ability of decorrelation, but it is rarely used in the polarization sensitive array. In this paper, an improved OMP algorithm based on polarization sensitive array is studied to estimate the pa- rameters of the air domain and the polarization domain. First, this algorithm remodels the signal receiving matrix of the polarization sensitive array, followed by using the proposed improved OMP algorithm to obtain the estimation results of spatial arrival angle. Then, the polarization parameters are estimated via the closed solution to a cost function of the mold constructor constraint, in which the estimated spatial arrival angle is substituted. Simulation results show that the proposed method can obtain good results in both coherent and incoherent signals and the estimation performance in the case of incoherent signals is generally better than the polarization ESPRIT algorithm and the modulus constraint MUSIC algorithm.