TY - GEN
T1 - Distance Estimation Algorithm Based on Multi-Antenna Signal Attenuation Model
AU - Wang, Jingjing
AU - Peng, Jishen
AU - Wang, Xianqing
AU - Hwang, Jun Gyu
AU - Park, Joon Goo
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/17
Y1 - 2021/8/17
N2 - Received Signal Strength Indicators (RSSI)-based indoor positioning technology is widely used in the field of Wi-Fi indoor positioning. However, the propagation of RSSI is still affected by indoor multipath, and we cannot obtain signals in some corner areas. This paper analyzes the distance relationship between the RSSI on each antenna of the receiver and the distance between transmitter and proposes a novel ranging algorithm based on multi-antenna RSSI measurements. This novel algorithm uses a Least Squares Method (LSM) on the basis of a signal attenuation model to optimize, eliminate the noise and redundancy of the original data and reduce the positioning error. Experimental results show that the indoor multi-antenna RSSI ranging based on the single Gaussian model has high fitting accuracy and applicability. The proposed approach achieves significant localization accuracy improvement over using the single antenna RSSI-based ranging method. Meanwhile, the algorithm improves the influence of multiple paths in a complex indoor environment on location, and the method can obtain more accurate ranging results.
AB - Received Signal Strength Indicators (RSSI)-based indoor positioning technology is widely used in the field of Wi-Fi indoor positioning. However, the propagation of RSSI is still affected by indoor multipath, and we cannot obtain signals in some corner areas. This paper analyzes the distance relationship between the RSSI on each antenna of the receiver and the distance between transmitter and proposes a novel ranging algorithm based on multi-antenna RSSI measurements. This novel algorithm uses a Least Squares Method (LSM) on the basis of a signal attenuation model to optimize, eliminate the noise and redundancy of the original data and reduce the positioning error. Experimental results show that the indoor multi-antenna RSSI ranging based on the single Gaussian model has high fitting accuracy and applicability. The proposed approach achieves significant localization accuracy improvement over using the single antenna RSSI-based ranging method. Meanwhile, the algorithm improves the influence of multiple paths in a complex indoor environment on location, and the method can obtain more accurate ranging results.
KW - Indoor ranging algorithm
KW - Least squares method
KW - Multi-Antenna
KW - Received Signal Strength Indicators
UR - https://www.scopus.com/pages/publications/85115642162
U2 - 10.1109/ICUFN49451.2021.9528555
DO - 10.1109/ICUFN49451.2021.9528555
M3 - Conference contribution
AN - SCOPUS:85115642162
T3 - International Conference on Ubiquitous and Future Networks, ICUFN
SP - 316
EP - 318
BT - ICUFN 2021 - 2021 12th International Conference on Ubiquitous and Future Networks
PB - IEEE Computer Society
T2 - 12th International Conference on Ubiquitous and Future Networks, ICUFN 2021
Y2 - 17 August 2021 through 20 August 2021
ER -