线阵相干源方位估计的波束域WSF算法实验验证

Experimental Study on Beam Space WSF Algorithm for Bearing Estimation

波束域加权子空间拟合 ( weighted subspace fitting—— WSF)算法保留了阵元域 WSF算法最佳的目标方位估计性能 ,而其运算量则有所降低。本文针对声呐系统中常用的线阵 ,通过计算机模拟实验和消声水池物理仿真实验研究了波束域 WSF算法解相干信源的性能。计算机模拟结果表明波束域 WSF算法可在低至 - 8d B的信噪比上分辨半常规束宽的强相关等功率信源 ,而水池实验则进一步表明算法可分辨不等功率相干信源 ,并在基阵校准系统误差后正确估计信源方位。

We extended the weighted subspace fitting (WSF) algorithm to beam space [3] . The beam space WSF algorithm maintains optimal performance in bearing estimation while reducing computational overhead. In this paper we carried out experiments in a water tank to verify the performance of this algorithm. A ten element uniform linear array was constructed for the experiments. Two strongly correlated signals with different amplitudes were transmitted from two transducers. Distance between these two transducers was adjusted so that the signals received by linear array are from different directions. For the data acquired from the linear array, three beams were formed directing at -0.2, 0, and 0.2 rad, respectively. Applying the beam space WSF algorithm to the beam outputs, these two strongly correlated sources were separated reliably and their incident directions were correctly estimated after effective compensation of possible system errors.