A Robust Converted Measurement Kalman Filter for Target Tracking

摘要：

This paper proposes a robust converted measurement Kalman filter (CMKF) algorithm to realize the target tracking with nonlinear measurement equations. At each processing index, the new algorithm chooses the more accurate state estimate from the state prediction and the sensor’s measurement. The new algorithm then computes the converted measurement’s error mean and the corresponding debiased converted measurement’s error covariance conditioned on the chosen state estimate. Simulation results demonstrate the new CMKF’s robust tracking performance as compared to the traditional DCMKF and MUCMKF. As a conclusion, the proposed algorithm can realize the target tracking with the non-linear measurement equations with well performance in different scenarios.

关键词： target tracking converted measurement Kalman filter (CMKF) robust CMKF non-linear filtering

作者: JIAO Lian-meng PAN Quan FENG Xiao-xue YANG Feng

作者单位: School of Automation, Northwest Polytechnical University, Xi’an Shaanxi Province, 710072

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 3754-3758

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）