传感器配准和多源融合是多传感器多目标跟踪系统中面临的两个重要问题。多传感器融合的精度一定程度上与传感器固有系统误差相关,为提高融合精度,需要进行多传感器配准。在多传感器多目标跟踪场景下,文中根据传感器量测噪声特性,通过公式推导实现了一种基于极大似然的联合多传感器配准与融合算法。该算法可同时在采样时刻间对传感器系统偏差和目标融合位置进行估计,并对传感器系统误差进行时间递推。仿真结果表明,文中算法具有较高的估计精度,可同时解决多传感器的配准与融合问题。

Sensor registration and multi-source fusion are important problems in the multi sensor-multi-target tracking systems. Multi-sensor fusion accuracy is related to sensors inherent system error to a certain extent, multi-sensor registration is required to improve the fusion accuracy. In multi-sensor-multi-target tracking scenarios, based on sensors measurement noise characteristic, this paper proposes a joint multi-sensor registration and fusion based on maximum likelihood algorithm which estimates sensors′system errors and targets′fusion position together. Simulation results show that this algorithm has high estimation precision, can solve the problem of multi-sensor registration and multi-sensor fusion at the same time.

TN957. 52