Dynamic Interference Source Tracking Based on Motion State Decomposition

Radio interference sources mounted on high-speed mobile platforms present a considerable challenge to accurate localization and tracking due to their wide-ranging and dynamic characteristics. This article tackles the intricate problem of tracking erratically maneuvering interference sources and introduces a dynamic tracking scheme for the spatial decomposition of motion states. Firstly, the proposed scheme decomposes the complex three-dimensional motion into three independent one-dimensional linear movements. This facilitates the concurrent application of interacting multiple model matching filters across all three dimensions, enabling precise characterization of the complex motion states. Secondly, an enhancement is made to the update process of the noise covariance matrix within the real-time noise estimator. Specifically, a time-varying exponential forgetting factor is incorporated to ensure the robustness of the adaptive cubature Kalman filter algorithm when combined with the noise estimator. Simulation results show that the proposed tracking scheme outperforms traditional methods in terms of both the speed of tracking error convergence and the fluctuations reduction. The improved accuracy and reliability of the proposed scheme position it as a promising approach for addressing the challenges associated with tracking dynamic radio interference sources on high-speed mobile platforms.