Hybrid TDOA/AOA Localization and Tracking Method for Multi-Station Cooperative Passive UAV Detection

To address geometric precision degradation and tracking divergence in single TDOA or AOA systems, this paper proposes a multi-station UAV tracking method integrating TDOA/AOA hybrid localization with nonlinear filtering to overcome precision degradation and tracking divergence in single-sensor systems. A Weighted Least Squares (WLS) method via pseudo-linearization provides reliable initial coordinate estimations, followed by an Unscented Kalman Filter (UKF) for continuous trajectory tracking. Simulations demonstrate that the proposed architecture eliminates network blind zones and robustly handles abrupt target maneuvers. Compared to the standard EKF, it rapidly suppresses peak RMSE to ~22 m and achieves a steady-state error of 10-15 m. This approach offers a high-precision, rapidly converging passive tracking solution for urban low-altitude defense.