High resolution time of arrival estimation algorithm for B5G indoor positioning

Abstract

In beyond 5G (B5G) indoor positioning time of arrival (TOA) positioning method is an important one. Base stations measure reference signals sent by terminals to calculate the TOA. The accuracy of position calculation is highly dependent on the TOA estimation resolution. This paper proposes a high-resolution TOA estimation algorithm based on Sounding Reference Signal (SRS) of 5G communication system. The algorithm achieves high resolution estimation by two steps. The Least Mean Square (LMS) adaptive filtering method is used as the first step to obtain the integer part of TOA, which is a coarse estimation of TOA. In the second step, we use weighted Generalized Cross-Correlation (GCC) algorithm to obtain the fractional part of TOA in frequency domain to get a more precise TOA estimation. Moreover, the stability of the estimated results is improved by the threshold value setting. The proposed algorithm is simulated in both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. The simulation results show that the TOA error achieves 0.56 m in AWGN and 0.96 m in Rayleigh fading channels for 80% of test samples respectively.