Unscented粒子滤波器及其在纯方位跟踪中的应用

Unscented Particle Filter for Bearings-Only Tracking

为处理纯方位跟踪(BOT)中的非线性问题,提出了一种Unscented粒子滤波(UPF)跟踪方法。在使用Unscented变换的基础上,利用UPF来加入最新的观测量并产生非线性粒子滤波(PF)的建议分布。结合纯方位跟踪模型,推导了UPF应用的具体算法步骤,使用匀速运动和机动目标两个BOT仿真实例,与其它滤波器进行了仿真对比,分析了跟踪性能和误差。仿真结果表明,对于纯方位跟踪问题,UPF不仅解决了扩展卡尔曼滤波器的线性化损失难题,而且与PF等粒子滤波器相比,具有更高的跟踪精度。

To solve the nonlinear problem in the Bearings-Only Tracking （BOT）, an Unscented Particle Filter（UPF） tracking method is proposed. Based on the Unscented transformation, the UPF is used to incorporate the most current observations and to generate the proposal distribution of the nonlinear Particle Filter （PF）. The specific application steps of the UPF are deduced combined with the BOT model. The comparisons are made between the UPF and other filters by simulations of the constant speed target and the maneuvering one in the BOT, where the performance and the root-mean-square error of the UPF are analyzed. The results show that the UPF not only solves the linearized loss problem in the extended Kalman filter, but also is more accurate than the PF in the BOT.