Distributed Anti-Eavesdropping Fusion Estimation Under Energy Constraints

In this article, we study the distributed fusion estimation problem with energy-constrained sensors in the presence of eavesdroppers, where smart sensors send their local estimates to a remote fusion center. To enhance privacy level, a novel encryption strategy is proposed by establishing an optimization problem, where the optimization objective is constructed by maximizing a combination of the fusion terminal estimation error covariance and the cost of encryption process in finite time domain. Meanwhile, the established problem is decomposed into several independent suboptimization problems under a relaxation condition, and a sufficient condition that depends on the system parameters is derived such that the suboptimization problems have optimal solutions. In this case, an optimal encryption strategy is designed with an analytical solution. Finally, a simulation example is given to show the effectiveness of the proposed methods.