基于改进纯方位跟踪一般方法的不稳定性,结合地形信息约束建立目标运动模型,提出一种带量测噪声的多方位测量的机动目标跟踪方法,在充分挖掘地形信息的基础上,引入伪测量并将其结合到目标状态方程和量测方程中,以改进量测信息的不连续性;然后,采用改进粒子滤波对受限运动目标的状态进行估计;最后进行的仿真分析表明,文中的方法不仅可以降低对观测者机动性的要求,而且可以提高目标状态估计的可观测性和跟踪精度。

For mitigating unstable behavior and low accuracy of common bearing-only tracking algorithm, the target motion models were built combined with terrain information constrain, and a new bearing-only tracking algorithm was proposed based on multi-bearing measurement with measurement noise. This method makes best use of terrain information and incorporates it into the equations of state and equations of measurement by using Pseudo-measurement, which mitigates discontinuity of measured information obtained by observer. Then, the improved particle filters were used for estimating the constrained moving target's state. The simulation results reveal that the method is useful, which can improve the estimation of observed state vector to improve tracking accuracy as well as lower requirement for the observer's maneuver.