2022 Fiscal Year Research-status Report
2D/3D indoor localization using multiple leaky coaxial cables over irregular wireless coverage environment.
| Project/Area Number |
20K04484
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| Research Institution | Okayama University |
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Principal Investigator |
侯 亜飛 岡山大学, 自然科学学域, 助教 (60598457)
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| Co-Investigator(Kenkyū-buntansha) |
上原 一浩 岡山大学, 自然科学研究科, 教授 (10221798)
冨里 繁 岡山大学, 自然科学研究科, 准教授 (60362951)
田野 哲 岡山大学, 自然科学研究科, 教授 (80378835)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | LCX localization / Particle filter / MIMO capacity / Spatial modulation / 2D/3D localization |
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| Outline of Annual Research Achievements |
In this year, a particle filter-based localization method is proposed. The proposed method uses LCXs to receive the signals from the target user. The TOAs of the signals at are utilized as the indicator for filtering in the localization process.
Different from localization methods in the previous work, the proposed particle filter-based method can be applied not only in the 2-D localization scenario but also in the 3-D localization scenario. The results show that the proposed method can achieve promising localization accuracy in both 2-D and 3-D scenarios.
Furthermore, we also investigated the capacity improvement of LCX system using spatial modulation with the on/off the LCX slots. We proposed a solution using Genetic Algorithms (GA) to find an optimal solution for On/off patterns.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
The results for 2D indoor multipath-rich environment showed the mean error of the conventional TDOA method is 1.8 m. However, for the particle filter -based method with the number of particles as 1000, the mean errors of the particle filter method can be 0.69 m. The 90% accuracy of the TDOA method is 2.9 m, and the 90% accuracy of the particle filter method is 0.89 m.
For 3D indoor multipath-rich environment, the mean value of the location error, when the number of particles (N) is set as 1000, is 0.94 m. When N is reduced to 100 and 500 which can have less computational complexity, the location errors are 2.47 m and 1.43 m respectively.
All results show that the localization accuracy of the proposed particle filter-based localization method for both 2D and 3D scenarios is promising.
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| Strategy for Future Research Activity |
In this year, the particle filter based interactive and iterative scheme has been proposed and evaluated. However, there exists many unknown questions. For example, how to set the optimal parameters for particle filter-based algorithm? How to reduce the number of particle filter and the complexity.
Till now, we only considered single user localization. The simultaneous indoor localization of multiple users is more important due to the coming of IoT era with massive devices. In addition, new antenna technologies such as reconfigurable intelligent surfaces (RIS) are emerging which can be combined for LCX-based indoor scenarios. These new factors will be researched in following years.
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| Causes of Carryover |
Due to the coronavirus situation, it is difficult to join some international conferences which saves the travel expenses.
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