Abstract
Nowadays transceiver-free (also referred to as device-free) localization using Received Signal Strength (RSS) is a hot topic for researchers due to its widespread applicability. However, RSS is easily affected by the indoor environment, resulting in a dense deployment of reference nodes. Some hybrid systems have already been proposed to help RSS localization, but most of them require additional hardware support. In order to solve this problem, in this paper, we propose two algorithms, which leverage the Packet Received Rate (PRR) to help RSS localization without additional hardware support. Moreover, we take the environment noise information into consideration by utilizing the Signal-to-Noise Ratio (SNR) which is based on the RSS and Noise Floor (NF) information instead of pure RSS. Thus, we can alleviate the noise effect in the environment and make our system more sensitive to the target. Specifically, when reference nodes are sparsely deployed and RSS is very weak, PRR and SNR can help in performing localization more accurately. Our BEYOND RSS system is based on sparse wireless sensor networks, wherein the experimental results show that the average localization error of our approach outperforms the pure RSS based approach by about 15.19%.
Original language | English |
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Pages (from-to) | 3866-3879 |
Number of pages | 16 |
Journal | IEEE Transactions on Mobile Computing |
Volume | 21 |
Issue number | 11 |
Early online date | 3 Mar 2021 |
DOIs | |
Publication status | Published - 1 Nov 2022 |
Funding
Natural Science Funds of Guangdong; 10.13039/501100001809; National Natural Science Foundation of China; Shenzhen Peacock Talent.
Keywords
- NF
- None-Line-of-Sight
- PRR
- RSS
- SNR
- Transceiver-free localization