单矢量水听器加窗直方图算法目标探测性能分析*

单个矢量水听器直方图算法具有良好的鲁棒性和目标方位估计性能,该文对直方图算法目标探测性能进行了分析和总结,并提出了一种基于目标方位估计的水中目标自主探测与跟踪算法,该算法可实现水中目标有无自主检测。仿真和消声水池测试结果表明,直方图算法实现目标自主跟踪所要求的信噪比需大于-7 dB,此时测向误差约为8°,-3 dB方位谱宽度在20°左右。海上试验数据分析表明,直方图算法对航速8.4 kn的水面航船在距离13.8 km范围内,可实现全程目标探测和跟踪,测向误差最优可达5?,在距离2 km时-3 dB方位谱宽度可达10°左右。

Analysis of target detection performance for a single vector hydrophone windowed histogram algorithm

The single vector hydrophone windowed histogram algorithm has good robustness and target azimuth estimation performance. This paper analyzes and summarizes the target detection performance of the windowed histogram algorithm, and an autonomous detection and tracking algorithm for underwater targets based on the estimated azimuth of the target was proposed. Computer simulation and anechoic tank test results show that the signal-to-noise ratio required by the windowed histogram algorithm for autonomous tracking needs to be greater than -7 dB ~ -6 dB. Under this condition, the estimated azimuth error and -3 dB beam width are about 8 ° and 20 °, respectively. The sea trial results show that under good hydrological conditions in the deep sea, the windowed histogram algorithm can achieve target detection and tracking for a surface ship with a speed of 8.4 kn within a range of 13.8 km. The optimal estimated azimuth error can reach 5 °, and the -3 dB beam width can reach about 10 ° at a distance of 2 km.