An attack-resilient distributed extended Kalman consensus filtering algorithm with applications to multi-UAV tracking problems

作     者：Yuru HU Wangyan LI Lifeng WU Zhensheng YU Yuru HU;Wangyan LI;Lifeng WU;Zhensheng YU

作者机构：College of ScienceUniversity of Shanghai for Science and TechnologyShanghai 200093China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2024年第25卷第8期

页      面：1110-1122页

核心收录：

学科分类：0808[工学-电气工程] 07[理学] 0835[工学-软件工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

基　　金：supported by the National Natural Science Foundation of China(Nos.62103283 and 12371308) 

主　　题：Extended Kalman consensus filtering Hypothesis testing Rectification strategy Multi-UAV tracking 

摘      要：This study investigates how the events of deception attacks are distributed during the fusion of multi-sensor nonlinear ***,a deception attack with limited energy(DALE)is introduced under the framework of distributed extended Kalman consensus filtering(DEKCF).Next,a hypothesis testing-based mechanism to detect the abnormal data generated by DALE,in the presence of the error term caused by the linearization of the nonlinear system,is *** the DALE is detected,a new rectification strategy can be triggered to recalibrate the abnormal data,restoring it to its normal ***,an attack-resilient DEKCF(AR-DEKCF)algorithm is proposed,and its fusion estimation errors are demonstrated to satisfy the mean square exponential boundedness performance,under appropriate ***,the effectiveness of the AR-DEKCF algorithm is confirmed through simulations involving multi-unmanned aerial vehicle(multi-UAV)tracking problems.