Fast direction of arrival algorithm based on vector-sensor arrays using wideband sources

An acoustic vector sensor （AVS） can capture more information than a conventional acoustic pressure sensor （APS）. As a result, more output channels are required when multiple AVS are formed into arrays, making processing the data stream computationally intense. This paper proposes a new algorithm based on the propagator method for wideband coherent sources that eliminates eigen-decomposition in order to reduce the computational burden. Data from simulations and lake trials showed that the new algorithm is valid： it resolves coherent sources, breaks left/right ambiguity, and allows inter element spacing to exceed a half-wavelength.     

基于自适应算法的单矢量传感器抗相干干扰

将矢量传感器组合指向性vs的零点对准已知的相干干扰方向,获得"干净"的目标信号,然后结合自适应算法抵消矢量传感器原始数据中各通道的相干干扰,达到抗相干干扰的目的.文中阐述了方法的原理,进行了多种情况下的仿真,并给出实验结果.仿真和实验结果表明该方法能有效抑制方位已知的相干干扰.     

Iterative algorithm of steered minimum variance and its application in weak targets detection

The steered covariance matrix (STCM) and its inverse matrix should be calculated in each beam for steered minimum variance (STMV). The inverse matrix needs complex computation and restricts its application in engineering. Combining the integration character of one-phase regressive filter with the iterative formula of inverse matrix, an STMV iterative algorithm is proposed. The computational cost of the iterative algorithm is reduced approximately to be 2/M times of the original one when there are M sensors, and is more advantaged for the realization of the algorithm in real time. Simulation results show that the STMV iterative algorithm can preserve the characters of STMV on high azimuth resolution and weak target detection while the computational cost reduced sharply. The analysis on sea trial data proves that the proposed algorithm can estimate each target’s azimuth even when the source powers differ in large scales or their bearings are very approximate.