有色量测噪声情况下的多传感器目标跟踪融合算法

目前已有的目标跟踪融合估计算法都是基于Kalman滤波的，而卡尔曼滤波估计算法要求系统过程噪声和量测噪声均为白色噪声，而实际的跟踪系统中量测噪声往往是有色噪声。针对上述问题，本文利用线性组合当前量测与下一时刻量测的量测扩增法，研究了有色量测噪声情况下的集中式、分布式多传感器目标跟踪融合算法。并对新的融合算法进行仿真分析，仿真结果表明新的融合算法具有良好的跟踪性能。

Track Fusion In Multi-Sensor System With Color Measurement Noise

The most track fusion algorithm are based on the kalman filter equations,where the process noise and the measurement noise are presumed white noise. However, the measurement noise in tracking systems are more often colored than white. Based on the ways of measurement augmented which by linear combinations of two consecutive measurement, a multi-sensor object tracking fusion algorithm with color measurement noise was proposed. Which was appropriate to the study of the track fusion estimation for the centralized, distributed multi-sensor. Simulation and compassion are given out. The results show a satisfied precision in their performance.