Kalman filter for multi-target tracking with integrated measurements subject to signal attenuation

Abstract

This paper is concerned with the problem of Kalman filtering (KF) for multi-target tracking systems with integrated measurements subject to signal attenuation. In order to estimate its own state, each target relies on locally available absolute measurements and relative measurements with other targets in the neighborhood. By enforcing each target to transmit its local estimates to the neighbors in a directed graph, a modified Kalman filter is proposed. By solving the Riccati-like difference equations, the gain matrices are determined by minimizing the trace of the upper bound matrix. A numerical example is provided to verify the effectiveness of the KF.