TY - GEN
T1 - A Joint Elliptic-AOA Based Localization Method with Weighted Iteration
AU - Ping, Zeyu
AU - Li, Renjie
AU - Zheng, Ziming
AU - Liang, Zhennan
AU - Song, Yuanyuan
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - Elliptic-AOA localization
KW - GDOP
KW - Kalman filter
KW - TDOA-AOA
KW - localization accuracy
KW - weighted fusion
UR - https://www.scopus.com/pages/publications/105032480093
U2 - 10.1109/IGARSS55030.2025.11313928
DO - 10.1109/IGARSS55030.2025.11313928
M3 - Conference contribution
AN - SCOPUS:105032480093
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 5697
EP - 5701
BT - IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2025
Y2 - 3 August 2025 through 8 August 2025
ER -