不完全量测下目标跟踪系统的容许量测噪声

Admissible Measurement Noise in Target Tracking with Incomplete Measurements

针对目标跟踪系统不可避免存在的量测值丢失的情况,研究了统计意义下基于不完全量测的估计误差协方差的性质,并分析了稳态滤波误差方差与量测噪声之间的关系。当传感器探测概率已知,在给定的误差方差约束下,给出了考虑不完全量测条件下滤波器的一种新算法,可使系统具有最大容许量测噪声强度,从而可降低对传感器精度的要求。数值算例和蒙特卡罗(Monto Carlo)仿真结果表明了该方法的有效性。

The properties of statistical error covariance matrix （ECM） with incomplete measurements were studied for the phenomenon of missing measurements which often occurs in target tracking. The relationship between the steady filtering error variance and the measurement noise with incomplete measurements was analyzed. While the detection probability was assumed to be known, a new filter algorithm with variance-constrained index was proposed which allowed the measurement noise intensity as high as possible, so the requirement of the sensor could decrease. In order to demonstrate the usefulness of the proposed design approach, a numerical example was presented as well as Monte Carlo simulation.