基于阵列扩展的改进PM的二维DOA估计

Improved PM in Two-dimensional DOA Estimation Based on Array Expansion

针对二维L型阵列参数估计过程中,由于低信噪比(signal-to-noise ratio,SNR)及小快拍数的不理想条件,使得传播算子算法(propagation method,PM)角度估计不准确,提出一种基于阵列扩展的改进PM算法的二维波达方向(direction of arrival,DOA)估计算法.该方法利用阵列的平移不变特性,对协方差矩阵进行扩展重排,并由此扩展协方差矩阵估计得到传播算子,将传播算子分块得到和阵列流型的新关系,进一步提高了估计性能,然后通过快速配对法实现俯仰角和方位角的配对,进而实现角度的精确估计.与现有的算法相比,该方法更适用于低SNR及小快拍数的情况,而且角度估计准确,无须谱搜索,工程应用价值更高.仿真结果显示了本文算法有较好的二维DOA估计性能.

To solve the problem of inaccurate estimation of propagation method( PM) under low signalto-noise ratio( SNR) and small snapshots,which exists in the process of two-dimensional L-shaped array parameter estimation, an improved PM in two-dimentional direction of arrival( DOA) estimation algorithm based on array expansion was proposed in this paper. In this method,the covariance matrix was extended and rearranged by using the rotation invariance characteristics and the propagator was got through the covariance matrix. Then the relationship was obtained between the block propagation operator and the array flow pattern by using the extending covariance matrix,which further improves the estimation performance. Then the elevation angle was matched with the azimuth angle through fast pairing method,in turn,an accurate estimation of the angle was achieved. Compared with the existing algorithms,the proposed method is more suitable,accurate and practicable,especially in the case of low SNR and small snapshots. Simulation experiments show that the proposed algorithm has better two-dimentional DOA estimation performance.