A practical adaptive nonlinear tracking algorithm with range rate measurement. (May 2018)

• Record Type: Journal Article
• Authors: Yang, Haiyan; Liu, Hongqiang; Zhou, Zhongliang; Xu, An
• Is Part Of: International journal of distributed sensor networks. Volume 14:Number 5(2018)
• Publication Date: 2018-05
• Subjects: Nonlinear filter -- measurement equation -- range rate -- adaptive filter -- target tracking -- cumulative sum detector; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147718776863
• Languages: English
• ISSNs: 1550-1329

Abstract

It is difficult to answer the problem whether the range rate measurement should be adopted to track a target in a tracking scenario. A practical adaptive nonlinear tracking algorithm with the range rate measurement is proposed, which avoids this problem and achieves good accuracy of target state estimation. First, three popular nonlinear filtering algorithms only with the position measurement are surveyed. Second, three popular nonlinear filtering algorithms with the position and range rate measurements are surveyed. Then, a novel tracking algorithm with range rate measurement is proposed based on the cumulative sum detector and the above two kinds of nonlinear algorithms. The results of simulation experiment demonstrate that the range rate measurement could reduce accuracy of the target state estimation in mismatch tracking scenarios. The results of simulation experiment also verify that the performance of proposed algorithm is better than the current state and the art interacting multiple-model algorithm and can well follow the state estimation output of the measurement equation matching the tracking scenario.