A TOA-DOA Hybrid Factor Graph-Based Technique for Multi-Target Geolocation and Tracking

In this article, we propose a new distributed sensors-based multi-target geolocation and tracking technique. The proposed technique is joint time-of-arrival (TOA) direction-of-arrival (DOA) factor graph (FG) for (FG-GE), which further combined with another FG extend Kalman filtering (FG-GE-EKF) tracking. Two-dimensional (2D) three-dimensional (3D) scenarios are considered. the FG-GE part, sensor association to solve matching problem, makes right correspondence between DOA/TOA information gathered by sensors each target. With technique, measured signals from targets can adequately be matched their corresponding FGs. Thereby, reduced multiple independent single target geolocation. addition, in 3D scenario, projected onto three orthogonal planes (x,y,z) coordinate. operation, decomposed into 2D problems. FG-GE-EKF whole system divided two steps: prediction step update step. step, predicted state obtained previous state. Then, utilize as prior information, also message exchanged FG-GE. estimates regarded observation used refine state, acquire current FG-GE-EKF, position estimation accuracy performance improved dramatically, without requiring excessively high computational effort.