基于单水听器的移动声源运动参数估计

发布时间：2018-03-02 18:11

本文选题：运动参数估计　切入点：时延估计　出处：《船舶力学》2017年11期 　论文类型：期刊论文

【摘要】：文章基于水声信道的多途结构,提出了一种利用舰船辐射噪声的单水听器声源运动参数估计方法。首先分析了自相关和倒谱多途时延估计方法,并针对传播水槽实验中随声源与单水听器距离增加自相关和倒谱时延峰信干比降低的问题,提出了基于自相关和倒谱的联合估计方法,提高了多途时延估计的稳健性;其次针对如何利用估计出的D-SR时延差这唯一信息进行运动参数估计的问题,通过逐步分析说明了径向匀速直线移动声源的运动参数估计问题可以在卡尔曼滤波(Kalman filter,KF)框架下进行求解;最后应用扩展卡尔曼滤波(extended Kalman filter,EKF)和迭代扩展卡尔曼滤波(iterated extended Kalman filter,IEKF)对水槽实验数据进行处理,所得结果表明:EKF和IEKF都能利用D-SR时延差信息估计出移动声源的距离、深度和速度,并且IEKF比EKF的跟踪效果更好,证明了方法的正确性和有效性。
[Abstract]:Based on the multipath structure of underwater acoustic channel, a method for estimating the motion parameters of a single hydrophone source using ship radiated noise is proposed. Firstly, autocorrelation and cepstrum multipath delay estimation methods are analyzed. Aiming at the problems of increasing autocorrelation with the distance between sound source and single hydrophone and decreasing the signal to interference ratio of Cepstrum, a joint estimation method based on autocorrelation and cepstrum is proposed to improve the robustness of multipath time delay estimation. Secondly, how to use the estimated D-SR delay difference, which is the unique information, to estimate the motion parameters, By stepwise analysis, it is shown that the motion parameter estimation problem of radial uniform linear moving sound source can be solved under the framework of Kalman filter KF (Kalman filter). Finally, extended Kalman filter (extended Kalman filter) and iterative extended extended Kalman filter (IEKF) are used to process the experimental data of the flume. The results show that both the IEKF and the EKF can estimate the distance, depth and velocity of the moving sound source by using D-SR delay difference information. The tracking effect of IEKF is better than that of EKF, which proves the correctness and effectiveness of the method.
【作者单位】：海军工程大学电子工程学院;
【基金】：国家自然科学基金资助项目(41576105)
【分类号】：TB56

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