Distributed Polynomial Set-Membership Fusion Estimation for Target Tracking Systems Under a Binary Encoding Scheme

In this article, a distributed polynomial set-membership fusion estimation approach is proposed for target tracking systems under a binary encoding scheme. Each distance measurement of the considered target is encoded via a binary encoding scheme to facilitate digital transmission. Based on the decoding signals, local estimators are designed by employing a polynomial set-membership estimation method. Furthermore, the effects of possible flipping bits occurring during the transmissions from the distance sensors to the local estimators are considered, and a detection scheme for flipping bits is presented by utilizing the obtained local estimation results. Subsequently, an optimal matrix-weighted distributed fusion estimator is developed in the $F$-radius sense of the zonotope restraining the global estimation error. Finally, simulation studies on a target tracking scenario are provided to demonstrate the effectiveness of the proposed approach.