A Joint Elliptic-AOA Based Localization Method with Weighted Iteration

In recent years, distributed radar systems have become a research hotspot for solving target localization problems due to their significant advantages, such as spatial diversity. Due to the problem and contradiction that the current radar target localization means cannot meet the target localization accuracy caused by increasingly complex jamming means and environment, this paper first analyzes the accuracy of target localization based on time difference of arrival-angle of arrival (TDOA-AOA) and Elliptic-AOA localization, considering range error, angle error and radar position error, and compares the localization accuracy of the two methods using azimuth or elevation angles. In order to improve the localization accuracy and anti-interference ability, this paper proposes a joint Elliptic-AOA localization method based on geometric dilution of precision (GDOP) weighted iteration to reduce its influence. The algorithm first applies Kalman filter to smooth localization results over multiple time steps, then weights the filtered results of multi-nodes based on GDOP for multi-nodes fusion, and iteratively updates the weights during the process. So, the target position can be obtained upon iterative convergence. In the end, simulations successfully verify the effectiveness and robustness of the algorithm in improving target localization accuracy.