基于目标相对位置的多传感器数据关联及传感器偏差估计（英文）

Sensor data association usingrelative positions among targets and bias estimation between separate sensors

多传感器数据关联是现代多传感器系统中的一个重要问题.多传感器数据关联即是确定不同传感器系统观测到的若干测量信号是否来源于同一个目标.传统的数据关联方法通过形成关联矩阵,来求取关联矩阵的最优解,但是容易受到传感器性能的影响.为了降低传感器性能对关联结果的影响,提出了一种新的通过采用比较传感器测量信号之间的相对位置并提取相对位置模式的方法来获得不同传感器系统对应的目标匹配对的方法,并给出了一种改进的适用于传感器目标信号关联的匹配算法.这种方法充分利用了测量信号之间相对位置的内在特性.仿真结果表明传感器偏差对于采用相对位置进行数据关联的方法基本没有影响,并且这种方法整体性能上有所提升.

Sensor data association is an important problem in modern multi-sensor systems. The purpose to solve this problem is to decide which measurements from the different sensors belong to the same target. The traditional methods for data association usually form the association matrix and find the optimal solution in different ways. These solutions are, however, sensitive to the characteristics of the sensors. A novel method which uses the relative positions among the targets and extracts the relative positions pattern to compare and search for the matching pairs between the separate sensor systems is proposed. An improved algorithm which is suitable for sensor data association using relative positions is also presented. The sensor bias has little influence upon this association algorithm due to the inherent characteristics of the relative positions. Simulation results show that association using relative positions is robust against sensor bias and has an overall improvement.