基于参考加速度的机动目标跟踪模型

Reference acceleration-based dynamic model for maneuvering target tracking

为准确描述目标机动时加速度动态特性,实时结合目标机动的先验知识和动态信息,提出一类基于参考加速度的机动目标动态模型。该模型假设机动加速度具有非对称的四重一致混合分布的概率密度函数。这种非均匀的特性使得模型的加速度噪声方差随着目标机动自适应调整。该文推导了适宜于Kalman滤波器应用的相应离散化模型,并给出了该模型与其他典型的机动目标模型的联系。针对典型的高机动目标跟踪问题的仿真试验表明,该模型比标准的Singer模型及"当前"模型具有更好的机动目标跟踪能力。

A reference acceleration-based model combining the prior knowledge and dynamic maneuvering information was developed to accurately describe the dynamics of maneuvering targets. The acceleration is assumed an asymmetric distribution with a quadruple-uniform mixture probability density. The asymmetry adaptively describes the acceleration＇s variation based on the target＇s maneuvers. A discretized Kalman filter is used for the analysis. And the connections between the proposed model and some other representative models are expatiated. Simulations show that the model performs better than the Singer model and the ＂current＂ model when maneuvers occur, during typical target tracking process.