TOPSIS Cooperative Positioning Quality Evaluation Cloud Model Integrating EWM And AHP
Cunle Zhang, Haonan Wang, Chengkai Tang, Baowang Lian · 2023
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.