Distributed Triangulation Filter for Target Motion Estimation via Bearing-Only Measurements

This paper introduces the novel consensus-based distributed spatial-temporal coordinated triangulation filter (CD-STCTF), a unified framework designed to overcome the fundamental challenge of achieving reliable and high-precision motion estimation of non-cooperative targets using bearing-only measurements in multi-agent systems. First, our approach centers on the spatial-temporal coordinated triangulation (STCT) model, which optimally integrates historical and spatial bearing information to transform the nonlinear problem into a robust, pseudo-linear state estimation problem. Second, this powerful geometric linearization is embedded within a consensus-on-information-matrix distributed architecture, ensuring robust operation and network consistency across multi-agent systems with sparse communication topologies. Third, a key technical feature is the incorporation of a dynamic measurement noise covariance matrix, which correctly models the distance-dependent uncertainty in angular measurements. Furthermore, we prove the global bounded stability of the CD-STCTF dynamic error. Simulation and real-world experimental results against existing distributed algorithms and the centralized Kalman filter (CKF) benchmark demonstrate that the CD-STCTF achieves superior estimation accuracy, faster convergence rates, and enhanced robustness and is comparable to the CKF, establishing its efficacy for high-performance cooperative bearing-only target motion estimation.