Human-to-Human Position Estimation System Using RSSI in Outdoor Environment
Methods to prevent collisions between people to avoid traffic accidents are receiving significant attention. To measure the position in the non-line-of-sight (NLOS) area, which cannot be directly visually recognized, position-measuring methods use wireless-communication-type GPS and propagation char...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/19/7621 |
| _version_ | 1827652965308039168 |
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| author | Takashi Yamamoto Tomoyuki Yamaguchi |
| author_facet | Takashi Yamamoto Tomoyuki Yamaguchi |
| author_sort | Takashi Yamamoto |
| collection | DOAJ |
| description | Methods to prevent collisions between people to avoid traffic accidents are receiving significant attention. To measure the position in the non-line-of-sight (NLOS) area, which cannot be directly visually recognized, position-measuring methods use wireless-communication-type GPS and propagation characteristics of radio signals, such as received signal strength indication (RSSI). However, conventional position estimation methods using RSSI require multiple receivers, which decreases the position estimation accuracy, owing to the presence of surrounding buildings. This study proposes a system to solve this challenge using a receiver and position estimation method based on RSSI MAP simulation and particle filter. Moreover, this study utilizes BLE peripheral/central functions capable of advertising as the transmitter/receiver. By using the advertising radio waves, our method provides a framework for estimating the position of unspecified transmitters. The effectiveness of the proposed system is evaluated in this study through simulations and experiments in actual environments. We obtained an error average of the distance to be 1.6 m from the simulations, which shows the precision of the proposed method. In the actual environment, the proposed method showed an error average of the distance to be 3.3 m. Furthermore, we evaluated the accuracy of the proposed method when both the transmitter and receiver are in motion, which can be considered as a moving person in the outdoor NLOS area. The result shows an error of 4.5 m. Consequently, we concluded that the accuracy was comparable when the transmitter is stationary and when it is moving. Compared with conventional path loss, the model can measure distances of 3 m to 10 m, whereas the proposed method can estimate the “position” with the same accuracy in an outdoor environment. In addition, it can be expected to be used as a collision avoidance system that confirms the presence of strangers in the NLOS area. |
| first_indexed | 2024-03-09T21:10:24Z |
| format | Article |
| id | doaj.art-be7d0dc0770a41adb29893ff63f85316 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:10:24Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-be7d0dc0770a41adb29893ff63f853162023-11-23T21:52:09ZengMDPI AGSensors1424-82202022-10-012219762110.3390/s22197621Human-to-Human Position Estimation System Using RSSI in Outdoor EnvironmentTakashi Yamamoto0Tomoyuki Yamaguchi1Master’s Programs in Intelligent and Mechanical Interaction Systems, University of Tsukuba, Tsukuba 305-8573, JapanFaculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba 305-8573, JapanMethods to prevent collisions between people to avoid traffic accidents are receiving significant attention. To measure the position in the non-line-of-sight (NLOS) area, which cannot be directly visually recognized, position-measuring methods use wireless-communication-type GPS and propagation characteristics of radio signals, such as received signal strength indication (RSSI). However, conventional position estimation methods using RSSI require multiple receivers, which decreases the position estimation accuracy, owing to the presence of surrounding buildings. This study proposes a system to solve this challenge using a receiver and position estimation method based on RSSI MAP simulation and particle filter. Moreover, this study utilizes BLE peripheral/central functions capable of advertising as the transmitter/receiver. By using the advertising radio waves, our method provides a framework for estimating the position of unspecified transmitters. The effectiveness of the proposed system is evaluated in this study through simulations and experiments in actual environments. We obtained an error average of the distance to be 1.6 m from the simulations, which shows the precision of the proposed method. In the actual environment, the proposed method showed an error average of the distance to be 3.3 m. Furthermore, we evaluated the accuracy of the proposed method when both the transmitter and receiver are in motion, which can be considered as a moving person in the outdoor NLOS area. The result shows an error of 4.5 m. Consequently, we concluded that the accuracy was comparable when the transmitter is stationary and when it is moving. Compared with conventional path loss, the model can measure distances of 3 m to 10 m, whereas the proposed method can estimate the “position” with the same accuracy in an outdoor environment. In addition, it can be expected to be used as a collision avoidance system that confirms the presence of strangers in the NLOS area.https://www.mdpi.com/1424-8220/22/19/7621received signal strength indicationoutdoor systemposition estimation |
| spellingShingle | Takashi Yamamoto Tomoyuki Yamaguchi Human-to-Human Position Estimation System Using RSSI in Outdoor Environment Sensors received signal strength indication outdoor system position estimation |
| title | Human-to-Human Position Estimation System Using RSSI in Outdoor Environment |
| title_full | Human-to-Human Position Estimation System Using RSSI in Outdoor Environment |
| title_fullStr | Human-to-Human Position Estimation System Using RSSI in Outdoor Environment |
| title_full_unstemmed | Human-to-Human Position Estimation System Using RSSI in Outdoor Environment |
| title_short | Human-to-Human Position Estimation System Using RSSI in Outdoor Environment |
| title_sort | human to human position estimation system using rssi in outdoor environment |
| topic | received signal strength indication outdoor system position estimation |
| url | https://www.mdpi.com/1424-8220/22/19/7621 |
| work_keys_str_mv | AT takashiyamamoto humantohumanpositionestimationsystemusingrssiinoutdoorenvironment AT tomoyukiyamaguchi humantohumanpositionestimationsystemusingrssiinoutdoorenvironment |