基于双观测站的水下机动目标被动跟踪

摘要

为了对水下机动目标进行航迹跟踪,采用双观测站被动跟踪系统,解决了单观测站利用纯方位角信息进行跟踪时的不可观测问题,建立了目标状态方程和被动观测方程.将扩展卡尔曼滤波(EKF)和无迹卡尔曼滤波(UKF)与交互式多模型算法OMM)相结合,应用于被动跟踪系统中.仿真结果表明,2种算法都能适用于水下机动目标被动跟踪.随着测量误差的增大,IMM-UKF算法比IMM-EKF算法表现出了更好的稳定性和更高的跟踪精度.%For tracking underwater maneuvering target,a passive tracking system with double observation station is used to solve the unobservable problem of single observation station due to tracking with bearing angle-only information.The target state equation and the passive observation equation are established.The extended Kalman filter(EKF) and the unscented Kalman filter(UKF) are combined respectively with the interactive multiple model(IMM) algorithm to serve the passive tracking system with double observation station.Simulation results show that both IMM-UKF and IMM-EKF algorithms can be applied to passive tracking of underwater maneuvering targets.The IMM-UKF algorithm exhibits higher stability and tracking accuracy than the IMM-EKF algorithm with the increase of measurement error.