The Toa Estimation of Cellular Network Signals Based on Machine Learning in Complex Urban Environments

Abstract

Abstract. The precision location-based services in complex environment is a challenge in the field of navigation and positioning. With the continuous development of wireless communication technology in recent years, cellular network signals such as LTE and 5G have emerged as unique advantages in navigation and positioning applications. This paper presents a time-of-arrival (TOA) estimation method based on machine learning, which can use cellular network signals to obtain accurate ranging results in low signal-to-noise ratio conditions. For this purpose, we first present the cellular network signals that can be applied in navigation and positioning. Then, we describe in detail the process of TOA estimation based on machine learning. Finally, we carried out vehicular experiments in an urban environment to test the performance of the proposed method. The test results demonstrate the feasibility of the proposed method and achieve metre-level ranging accuracy.