道路约束条件下的地面运动目标跟踪

摘要

The effective use of road data is probably the most important way that ground target tracking performance can be improved. This paper presents a road constraint algorithm based on Kalmanfilter theory for ground moving target tracking. Road segment model and road segment assignment algorithm are described. An process noise analysis is given about road constrain. Adapted algorithm to the adjacent road is introduced when the state passes a junction. According to the corresponding road parameters,target constrained estimation is modified under Maximum A Posteriori (MAP)solution.The simulation results show that the proposed algorithm is very effective.Quantitative analysis shows that time complexity of the algorithm is acceptable.%有效使用道路信息能显著提高地面运动目标跟踪性能。基于卡尔曼滤波理论，提出了道路约束条件下的滤波方法。首先建立了描述道路网中路段的数学模型，给出了将目标分配于道路的定位算法；然后推导了道路约束条件下的过程噪声矩阵；提出了路段切换时状态修正公式；在道路约束最大后验概率估计准则下，根据道路参数修正状态与协方差。蒙特卡洛仿真结果证明了该算法的优越性能，且定量分析表明其计算量是可接受的。