TY - GEN
T1 - TOPSIS Cooperative Positioning Quality Evaluation Cloud Model Integrating EWM and AHP
AU - Zhang, Cunle
AU - Wang, Haonan
AU - Tang, Chengkai
AU - Lian, Baowang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The intelligent development of the integration of space, space, and sea cannot be achieved without navigation and positioning services. The current collaborative positioning solutions are rich and complex, with varying evaluations of positioning performance, and there is an urgent need to evaluate them. This study proposes evaluation methods from the nodes, links, algorithms, and hardware of collaborative positioning systems, provides quality evaluation levels, and constructs an evaluation architecture that integrates tomography analysis (AHP), entropy weight analysis (EWM), ideal advantage and disadvantage distance analysis (TOPSIS), and cloud model theory (CM). This framework has been evaluated and applied as an example through the collaborative positioning experiment of unmanned aerial vehicle clusters. Combining AHP-EWM with multi-dimensional TOPSIS cloud model for evaluation provides a scientific new approach for performance evaluation and provides a scientific basis for decision-making and improvement of actual positioning schemes.
AB - The intelligent development of the integration of space, space, and sea cannot be achieved without navigation and positioning services. The current collaborative positioning solutions are rich and complex, with varying evaluations of positioning performance, and there is an urgent need to evaluate them. This study proposes evaluation methods from the nodes, links, algorithms, and hardware of collaborative positioning systems, provides quality evaluation levels, and constructs an evaluation architecture that integrates tomography analysis (AHP), entropy weight analysis (EWM), ideal advantage and disadvantage distance analysis (TOPSIS), and cloud model theory (CM). This framework has been evaluated and applied as an example through the collaborative positioning experiment of unmanned aerial vehicle clusters. Combining AHP-EWM with multi-dimensional TOPSIS cloud model for evaluation provides a scientific new approach for performance evaluation and provides a scientific basis for decision-making and improvement of actual positioning schemes.
KW - AHP
KW - Cloud Model
KW - EWM
KW - Positioning Quality Assessment
KW - TOPSIS
UR - http://www.scopus.com/inward/record.url?scp=85184856946&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC59353.2023.10400275
DO - 10.1109/ICSPCC59353.2023.10400275
M3 - 会议稿件
AN - SCOPUS:85184856946
T3 - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
BT - Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
Y2 - 14 November 2023 through 17 November 2023
ER -