TY - GEN
T1 - MM-APS-SCENT
T2 - 2023 IEEE/CIC International Conference on Communications in China, ICCC 2023
AU - Li, Xudong
AU - Fan, Ye
AU - Yao, Rugui
AU - Wang, Peng
AU - Zuo, Xiaoya
AU - Wang, Jiayu
AU - Xie, Yi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - To achieve better localization accuracy in a complex electromagnetic environment with multiple modulated signals, in this paper, an end-to-end joint analysis framework is presented. This framework is target-transmitter-localization-oriented and apriori-signal-parameter-enabled. Specifically, on the one hand, given that the localization accuracy of existing algorithms is generally influenced by multiple factors such as calculated complexity, channel fading, and unavailable signal parameters in a complex electromagnetic environment, signal parameter estimation is considered and employed to overcome above difficulties for enhancement of the localization accuracy. To facilitate signal parameter estimation, mixed signals are transformed into a time-frequency image using smoothed-pseudo-Wigner-Vile distribution and image processing. On the other hand, based on the Min-Max algorithm and area partition strategy, an improved weighted centroid localization algorithm, MM-APS-SCENT, is proposed. For the MM-APS-SCENT algorithm, we further devise an area partition criterion to fulfill the superior localization accuracy. Finally, numerical results prove the correctness of theoretical analysis and show effectiveness, reliability, and robustness of the proposed MM-APS-SCENT algorithm compared with Min-Max, E-Min-Max, and weighted-cent algorithms.
AB - To achieve better localization accuracy in a complex electromagnetic environment with multiple modulated signals, in this paper, an end-to-end joint analysis framework is presented. This framework is target-transmitter-localization-oriented and apriori-signal-parameter-enabled. Specifically, on the one hand, given that the localization accuracy of existing algorithms is generally influenced by multiple factors such as calculated complexity, channel fading, and unavailable signal parameters in a complex electromagnetic environment, signal parameter estimation is considered and employed to overcome above difficulties for enhancement of the localization accuracy. To facilitate signal parameter estimation, mixed signals are transformed into a time-frequency image using smoothed-pseudo-Wigner-Vile distribution and image processing. On the other hand, based on the Min-Max algorithm and area partition strategy, an improved weighted centroid localization algorithm, MM-APS-SCENT, is proposed. For the MM-APS-SCENT algorithm, we further devise an area partition criterion to fulfill the superior localization accuracy. Finally, numerical results prove the correctness of theoretical analysis and show effectiveness, reliability, and robustness of the proposed MM-APS-SCENT algorithm compared with Min-Max, E-Min-Max, and weighted-cent algorithms.
KW - Area partition strategy
KW - end-to-end
KW - localization error
KW - signal parameter estimation
KW - target transmitter localization
UR - http://www.scopus.com/inward/record.url?scp=85173021192&partnerID=8YFLogxK
U2 - 10.1109/ICCC57788.2023.10233492
DO - 10.1109/ICCC57788.2023.10233492
M3 - 会议稿件
AN - SCOPUS:85173021192
T3 - 2023 IEEE/CIC International Conference on Communications in China, ICCC 2023
BT - 2023 IEEE/CIC International Conference on Communications in China, ICCC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 August 2023 through 12 August 2023
ER -