Research on Asynchronous Information Fusion Technology of the Distributed Active/Passive Imaging Detection System

Abstract

In the process of target cooperative tracking of the distributed multi-imaging detection system, aiming at the problem of asynchronous measurement information from different detectors, a distributed Asynchronous and Heterogeneous Information Matrix Fusion algorithm based on the Cubature Kalman Filter (CKF-AHIMF) is proposed. According to the Local Detector Driven Communication (LDDC) method and CKF nonlinear mapping, IMF distributed fusion algorithm is generalized into nonlinear, asynchronous, and heterogeneous cases to integrate the information from a multi-imaging detection system and to obtain global high-precision target trajectory. Through the digital simulation, it is verified that the CKF-AHIMF algorithm under the LDDC method proposed in this paper is more effective and has higher tracking accuracy than other distributed fusion algorithms in dealing with the problem of target cooperative tracking under asynchronous information from local imaging detectors, which is also valid to implement in precision detection and guidance system.