A Novel Distributed Fusion Algorithm for Maneuvering Target Tracking with Angle-Only Sensors

A novel distributed fusion algorithm is proposed to address the challenge of maneuvering target tracking using angle-only sensors. Firstly, the square root cubature Kalman filter (SRCKF) is employed to estimate the target's position. Secondly, a distributed fusion architecture for multi-sensor systems is developed to form a distributed SRCKF (DSRCKF) method. Subsequently, a novel covariance intersection (NCI) algorithm is introduced, which formulates the fusion weight selection as a semidefinite programming problem. Additionally, the interacting multiple model (IMM) approach is integrated to achieve maneuvering target tracking, effectively mitigating filter divergence caused by mismatched target motion models. Finally, simulation experiments are performed to evaluate the tracking accuracy of the proposed IMM-DSRCKF-NCI algorithm, showcasing its superior performance and confirming its effectiveness.