摘要
针对目标跟踪定位中,观测噪声等价为白噪声造成预测目标位置精度下降的问题,提出了评估精度下降程度的方法。首先利用Cramer-Rao下界理论给出估计精度上限,然后利用成型滤波器、卡尔曼滤波理论和统计分析法给出简化滤波器的实际估计精度,最后通过仿真,比较了实际估计精度与估计精度上限的差,证明当滤波时间大于2 s后,次优滤波器和最优滤波器的滤波精度差小于20%。
In target tracking and locating,the colored measurement noise is always equivalent to white noise when predicting the aiming point,which causes the deteriorated predicting accuracy.To evaluate the degree of the deterioration,the upper bound of the accuracy of the predicted target position is deduced using the Cramer-Rao lower bound theory.Based on the theories of shaping filtering and kalman filtering and statistics analysis,the actual prediction error of the simplified filter is presented,and compared with the upper limit of the estimate accuracy in simulations,the results show that the difference between them is less than 20% with enough filtering time（2 s）,which verify the feasibility of the simplified filter.
出处
《武汉理工大学学报》
CAS
CSCD
北大核心
2010年第15期108-113,118,共7页
Journal of Wuhan University of Technology
基金
湖北省自然科学基金(2009CDB274)
关键词
目标跟踪
有色测量噪声
成型滤波器
解耦滤波器
target tracking
colored measurement noise
shaping filter
decoupled filter
