TY - GEN
T1 - A Distributed Direct Position Determination Method with Optimal Sensor Selection
AU - Yang, Yuenan
AU - Sun, Yandong
AU - Liu, Qing
AU - Xie, Jian
AU - Han, Chuang
AU - Wang, Ling
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Passive localization plays a vital role in both military and civilian applications due to its high concealment and long-range detection capabilities. However, traditional two-step localization methods suffer from error accumulation and sub-optimal performance, especially in low-signal to noise ratio (SNR) scenarios. To address these issues, this paper proposes a distributed direct position determination (DDPD) method based on optimal sensor selection in wireless sensor networks. The method minimizes the trace of the Cramér-Rao lower bound (CRLB) to select the most effective sensor nodes, thereby enhancing localization accuracy and reducing system overhead. Simulation results indicate that the proposed method offers improved positioning accuracy while reducing both communication and computational overhead.
AB - Passive localization plays a vital role in both military and civilian applications due to its high concealment and long-range detection capabilities. However, traditional two-step localization methods suffer from error accumulation and sub-optimal performance, especially in low-signal to noise ratio (SNR) scenarios. To address these issues, this paper proposes a distributed direct position determination (DDPD) method based on optimal sensor selection in wireless sensor networks. The method minimizes the trace of the Cramér-Rao lower bound (CRLB) to select the most effective sensor nodes, thereby enhancing localization accuracy and reducing system overhead. Simulation results indicate that the proposed method offers improved positioning accuracy while reducing both communication and computational overhead.
KW - Cramér-Rao lower bound
KW - distributed direct position determination
KW - sensor selection
KW - wireless sensor network
UR - https://www.scopus.com/pages/publications/105021488845
U2 - 10.1109/ICSPCC66825.2025.11194640
DO - 10.1109/ICSPCC66825.2025.11194640
M3 - 会议稿件
AN - SCOPUS:105021488845
T3 - Proceedings of 2025 IEEE 15th International Conference on Signal Processing, Communications and Computing, ICSPCC 2025
BT - Proceedings of 2025 IEEE 15th International Conference on Signal Processing, Communications and Computing, ICSPCC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2025
Y2 - 18 July 2025 through 21 July 2025
ER -