Distance Estimation Algorithm Based on Multi-Antenna Signal Attenuation Model

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.