Square-Root Cubature Information Hybrid Consensus Filter With Correlated Noise and Its Applications in Camera Networks

Abstract

This paper proposes a hybrid consensus-based square-root cubature information filter for target tracking in camera networks in the case that the process and measurement noises are correlated with each other at the same time. To the best of our knowledge, this is the first work that shows how to utilize the square-root cubature information filter with correlated noise at the same time to track the target in camera networks. This paper first decouples the correlation and rearranges the state transition equation to a new one. Then, apply square-root cubature information filter based on the new state transition equation and the original measurement equation to proposed a hybrid consensus-based square-root cubature information filter with correlated noise (SCHF-CN). What’s more, it is proved that the proposed algorithm is stable via the consistency of estimates. The simulation results demonstrate the superior performance of the proposed SCHF-CN as compared to other algorithms via applications about the target tracking in camera networks.