Abstract
This paper is concerned with the networked distributed fusion estimation problem under denial-of-service (DoS) attacks, where the noise covariances are unknown but bounded, and the distribution information of DoS attacks is not required to be known. Based on the dimensionality reduction and compensation model, the local Kalman filter (LKF) with unknown covariances is designed by the maximum and minimum robust estimation criterion, while the distributed fusion Kalman filter (DFKF) is derived from the optimal weighted fusion criterion. Moreover, the robustness of the developed DFKF is also analyzed in the presence of DoS attacks. Finally, an illustrative example is exploited to demonstrate the effectiveness of the proposed methods.
Highlights
W ITH the development of sensors and computer technology, the multi-sensor fusion estimation (MFE) problem has attracted considerable interest, due primarily to its extensive applications in various fields including moving target tracking [1], signal processing [2] and industrial monitor [3]
The recent years have witnessed a surge of research interest in networked multi-sensor fusion estimation (NMFE) problems [12] - [19], where the measurement information can be sent to the fusion center (FC) via the wired or wireless communication networks
Though the dimensionality reduction fusion estimation problem under bandwidth constrains and DoS attacks were discussed in our previous work [24] and [26], the above works focused on the communication uncertainties between the local estimates and the FC, while the uncertain communication problem in this paper is from the sensor measurements that may suffer DoS attacks and bandwidth constraints
Summary
W ITH the development of sensors and computer technology, the multi-sensor fusion estimation (MFE) problem has attracted considerable interest, due primarily to its extensive applications in various fields including moving target tracking [1], signal processing [2] and industrial monitor [3]. Though the dimensionality reduction fusion estimation problem under bandwidth constrains and DoS attacks were discussed in our previous work [24] and [26], the above works focused on the communication uncertainties between the local estimates and the FC, while the uncertain communication problem in this paper is from the sensor measurements that may suffer DoS attacks and bandwidth constraints In this case, the place to reducing the dimensionality and the design of compensation strategy are different from [24] and [26]. The contribution of this paper can be summarized as follows: i) A unified compensation model is proposed to reduce the information loss caused by DoS attacks and bandwidth constraints; ii) A recursively DFKF is designed in the presence of uncertain covariances, and the robustness is guaranteed by establishing a positive semidefinite decision problem and can be solved by the Lyapunov equation. E {·} is the mathematical expectation, and x⊥y denotes that x and y are orthogonal vectors
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
