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Drone Controller Localization Based on RSSI Ratio

delete2023-05-29
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OA
AI
Y
Yuhong Wang *
Y
Yonghong Zeng
S
Sumei Sun
P
Peng Hui Tan
Y
Yugang Ma
E
Ernest Kurniawan
DOI:10.3390/s23115163delete
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摘要

摘要

En 中文
We proposed two methods for the localization of drone controllers based on received signal strength indicator (RSSI) ratios: the RSSI ratio fingerprint method and the model-based RSSI ratio algorithm. To evaluate the performance of our proposed algorithms, we conducted both simulations and field trials. The simulation results show that our two proposed RSSI-ratio-based localization methods outperformed the distance mapping algorithm proposed in literature when tested in a WLAN channel. Moreover, increasing the number of sensors improved the localization performance. Averaging a number of RSSI ratio samples also improved the performance in propagation channels that did not exhibit location-dependent fading effects. However, in channels with location-dependent fading effects, averaging a number of RSSI ratio samples did not significantly improve the localization performance. Additionally, reducing the grid size improved the performance in channels with small shadowing factor values, but this only resulted in marginal gains in channels with larger shadowing factors. Our field trial results align with the simulation results in a two-ray ground reflection (TRGR) channel. Our methods provide a robust and effective solution for the localization of drone controllers using RSSI ratios.
Keyword:
localization
RSSI fingerprint
two-ray ground reflection
WLAN channel
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期刊

Sensors 封面图
Sensors
IF:
3.5
论文数:
7.2W
被引数:
20.9W

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agency for science technology & research (a*star)
学者数:
2.2W
论文数: 1.9W
被引数: 57
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