Improving Localization Accuracy Through Optimal Selection Strategy

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出版年:Electronics vol. 14, no. 1 (2025), p. 172
第一著者: Wu, Na
その他の著者: Yan, Xiaozhen, Luo, Qinghua, Xing, Yuexiu
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MDPI AG
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024 7 |a 10.3390/electronics14010172  |2 doi 
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100 1 |a Wu, Na  |u School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; <email>wuna@njupt.edu.cn</email> (N.W.); <email>yxxing@njupt.edu.cn</email> (Y.X.) 
245 1 |a Improving Localization Accuracy Through Optimal Selection Strategy 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a A localization system is essential for providing crucial position information in various applications, such as three-dimensional (3D) warehousing, smart cities, uncrewed aerial vehicle (UAV) control, and other services that heavily rely on accurate localization. However, the transmission of wireless signals can be impacted by diverse environmental factors, leading to decreased accuracy in determining localization in scenarios involving multiple signal paths, None Line of Sight (NLOS) situations, and different types of interference. In some cases, this may render the localization system unsuitable for subsequent applications. To enhance the localization accuracy, we propose a 3D localization method using an optimization selection strategy. With this method, we make the following innovations: (1) We utilize an evaluation of feature points to minimize the negative impact of NLOS. (2) Through the backward assessment and the optimal selection of distance estimations, we obtain a more accurate localization result. In more detail, our approach implements a specific strategy for distance estimation, followed by defining the feature points within the localization field and selecting the most optimized one. Subsequently, using the chosen feature points, we evaluate the quality of the distances in reverse. We then select suitable distance estimation outcomes for further localization calculations. Ultimately, by employing the proposed 3D localization technique, we achieve a highly precise localization result. We perform simulations and experiments to assess the presented localization system. More specifically, compared with certain strategies, we improve the localization accuracy by 58.33% and 43.83% using the selection strategy. Compared with the other methods, we enhance the localization accuracy from 17.94% to 32.54%. The results from these evaluations demonstrate that our method significantly enhances 3D localization accuracy. 
653 |a Propagation 
653 |a Localization method 
653 |a Accuracy 
653 |a Localization 
653 |a Signal paths 
653 |a Maximum likelihood method 
653 |a Optimization 
700 1 |a Yan, Xiaozhen  |u School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China; <email>luoqinghua80@hit.edu.cn</email> 
700 1 |a Luo, Qinghua  |u School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China; <email>luoqinghua80@hit.edu.cn</email> 
700 1 |a Xing, Yuexiu  |u School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China; <email>wuna@njupt.edu.cn</email> (N.W.); <email>yxxing@njupt.edu.cn</email> (Y.X.) 
773 0 |t Electronics  |g vol. 14, no. 1 (2025), p. 172 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3153797765/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3153797765/fulltextwithgraphics/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
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