De-correlated unbiased sequential filtering based on best unbiased linear estimation for target tracking in Doppler radar

被引:10
|
作者
Peng Han [1 ]
Cheng Ting [1 ]
Li Xi [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Peoples R China
关键词
Kalman filter; best linear unbiased estimation (BLUE); measurement conversion; sequential filter; CONVERTED MEASUREMENTS; KALMAN FILTER; RANGE; ALGORITHM;
D O I
10.23919/JSEE.2020.000089
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In target tracking applications, the Doppler measurement contains information of the target range rate, which has the potential capability to improve the tracking performance. However, the nonlinear degree between the measurement and the target state increases with the introduction of the Doppler measurement. Therefore, target tracking in the Doppler radar is a nonlinear filtering problem. In order to handle this problem, the Kalman filter form of best linear unbiased estimation (BLUE) with position measurements is proposed, which is combined with the sequential filtering algorithm to handle the Doppler measurement further, where the statistic characteristic of the converted measurement error is calculated based on the predicted information in the sequential filter. Moreover, the algorithm is extended to the maneuvering target tracking case, where the interacting multiple model (IMM) algorithm is used as the basic framework and the model probabilities are updated according to the BLUE position filter and the sequential filter, and the final estimation is a weighted sum of the outputs from the sequential filters and the model probabilities. Simulation results show that compared with existing approaches, the proposed algorithm can realize target tracking with preferable tracking precision and the extended method can achieve effective maneuvering target tracking.
引用
收藏
页码:1167 / 1177
页数:11
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