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

• 来源期刊: 系统工程与电子技术（英文版）
• 年，卷（期）: 2020,（6）
• 所属期刊栏目: DEFENCE ELECTRONICS TECHNOLOGY
• 页码范围: 1167-1177
• 页数: 11页
• 语种: 英文
• DOI: 10.23919/JSEE.2020.000089

摘要

In target tracking applications,the Doppler measure-ment 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 sequentialfiltering algorithm to handle the Doppler measure-ment further,where the statistic characteristic of the converted measurement error is calculated based on the predicted informa-tion 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.