水下无源目标运动分析的修正扩展卡尔曼滤波方法
Study of underwater passive Motion Target Analysis (TMA) in revise extend Kalman filter
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摘要: 以水下已知固定深度的三维情形为例,用修正的扩展卡尔曼滤波(EKF)方法探讨了无源目标运动分析(以下简称TMA)问题。首先以无源声呐对目标的方位角、俯仰角和频率测量为依据,建立动态系统模型。然后,从非线性的测量方程入手,对新息以伪线性的处理,推导出一组修正的EKF递推方程组。文中为增加滤波器的稳定性,采取批数据处理的手段,而使滤波效果更加平稳。计算机仿真结果表明:修正的EKF方法所得的误差曲线收敛较好,且误差较小,能有效地提高水下无源TMA问题中的参数估计精度。Abstract: The method of the revise Extend Kalman Filter (EKF) is used in the problem passive TMA of a constant known depth in three dimensions. The model of motive system is made in the light of measurements of target bearings, elevation and frequency by passive sonar. Pseudo-linear method is used in new information due to nonlinear measurement equation. Then revise EKF equation is gained. In the other hand, data is divided in to groups in adding stability of filter. Simulation shows that this algorithm can gain effective parameter estimation which error covariance curves is reduced rapidly, thus this passive TMA of precise estimation can be realized in this algorithm.