Research on the Quantitative Relationship Between Positioning Error and Coherent Synthesis Success Rate in a Moving Platform Distributed Coherent Synthesis System

Distributed coherent synthesis on dynamic platforms suffers from phase misalignment and significantly reduced synthesis efficiency due to navigation errors and communication delays. To address this challenge and dramatically enhance the synthesis efficiency, this paper proposes an “error-performance” quantification framework and corresponding compensation methods: (1) Phase compensation strategy: Adaptive Kalman Filter (AKF) with a multi-index fusion-based adaptive factor derived from novelty sequences, enabling intelligent switching between predictive and robust modes for improved phase compensation; (2) Positioning error modeling method: Employing an adaptive reverse-adaptive robust Kalman filter (ARKF) to synthesize error trajectories, with standard deviation σ as the primary control parameter. Monte Carlo simulations establish a quantitative relationship between positioning error standard deviation (σ) and coherent synthesis success rate: Under a 3-transmitter configuration, success rate ≥ 95% when σ ≤ 100 mm; The 100–237.3 mm range constitutes a transition zone where success rate decreases from 95% to 80%; when σ ≥ 460 mm, the success rate stabilizes at 56–58%. The core conclusion indicates that when σ ≤ 237.3 mm, the system achieves high coherent synthesis efficiency with 80% probability. This paper aims to establish a cross-platform transferable error-performance quantification framework, providing a direct reference for navigational accuracy selection in distributed coherent systems.