DoA-LF: A Location Fingerprint Positioning Algorithm with Millimeter-Wave

TL;DR

This paper introduces DoA-LF, a novel indoor positioning algorithm using millimeter-wave signals and direction of arrival data, demonstrating reduced errors through simulations and analysis of various influencing factors.

Contribution

The paper proposes a new LF positioning method with mmWave that incorporates DoA information, enhancing accuracy over traditional RF-based methods.

Findings

mmWave signals reduce positioning error compared to lower frequency signals

accurate DoA estimation significantly improves positioning accuracy

simulation results confirm the effectiveness of the proposed method

Abstract

Location fingerprint (LF) has been widely applied in indoor positioning. However, the existing studies on LF mostly focus on the fingerprint of WiFi below 6 GHz, bluetooth, ultra wideband (UWB), etc. The LF with millimeter-wave (mmWave) was rarely addressed. Since mmWave has the characteristics of narrow beam, fast signal attenuation and wide bandwidth, etc., the positioning error can be reduced. In this paper, an LF positioning method with mmWave is proposed, which is named as DoA-LF. Besides received signal strength indicator (RSSI) of access points (APs), the fingerprint database contains direction of arrival (DoA) information of APs, which is obtained via DoA estimation. Then the impact of the number of APs, the interval of reference points (RPs), the channel model of mmWave and the error of DoA estimation algorithm on positioning error is analyzed with Cramer-Rao lower bound (CRLB). Finally, the proposed DoA-LF algorithm with mmWave is verified through simulations. The simulation results have proved that mmWave can reduce the positioning error due to the fact that mmWave has larger path loss exponent and smaller variance of shadow fading compared with low frequency signals. Besides, accurate DoA estimation can reduce the positioning error.