单矢量水听器水中多目标方位跟踪方法

摘要

The direction of arrival (DOA) of multiple targets was acquired by solving non-liner correlation equations involving acoustic pressure and particle velocity with quantum particle swarm algorithm.In order to improve the precision, the DOA tracks of multiple targets were fitted with the method of least squares, the prediction model was found and then the DOA tracks were optimized by Kalman filter.The results indicate that the DOA of multiple targets can be resolved with the single vector hydrophone and the results should be expressed by statistic characteristics.The maximum number of unknown sources is 7.As the number increases, the DOA error is more serious.When the signal to noise ratio is higher, the resolution ratio and precision are also higher and the deviation is smaller.More importantly, the precision of DOA can be improved effectively by the method of data fitting and the Kalman filter.%采用量子粒子群求解声压和质点振速组成的非线性相关方程组,实现多目标声源方位的估计.为提高精度,应用最小二乘法对测量结果进行拟合并建立预测模型,通过卡尔曼滤波对方位轨迹进行优化.结果表明:单矢量水听器能够同时分辨多个目标方位,解算结果应使用统计特性表示;采用本方法最多能分辨7个目标,目标个数越多,方位误差越大;信噪比越高,分辨率和精度越高,偏差越小;通过数据拟合然后卡尔曼滤波的方法能够有效提高目标方位跟踪精度.