@inproceedings{75f2cd65eda54532b8a2abc808861e37,
title = "Fusion tracking algorithm of active and passive target based on Gauss-Markove estimate",
abstract = "In order to improve the accuracy of target tracking for passive and active sensor detection, an algorithm based on Gauss-Markove estimate is presented. Active state estimation and passive estimation are operated respectively. By minimizing the error covariance matrix, the Gauss-Markove estimate is obtained and the passive estimation and active estimation are fused with weighted least square method. Monte-Carlo simulation results illustrate that the proposed algorithm can efficiently improve the accuracy of state estimation compared with active estimation. Presented method may be useful in target tracking and weapon strike application.",
keywords = "Gauss-Markove estimate, Kalman filter, Target tracking, active and passive cooperative detection",
author = "Shasha Ma and Haiyan Wang and Xiaohong Shen and Zhenxin Sun and Ning Sun",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 5th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2022 ; Conference date: 16-12-2022 Through 18-12-2022",
year = "2022",
doi = "10.1109/IMCEC55388.2022.10019853",
language = "英语",
series = "IMCEC 2022 - IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "946--950",
editor = "Bing Xu and Bing Xu",
booktitle = "IMCEC 2022 - IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
}