On Application of the Correlation Vectors Subspace Method for 2-Dimensional Angle-Delay Estimation in Multipath OFDM Channels
Elpiniki P. Tsakalaki, Jörg Schäfer · 2018
Indoor localization systems often necessitate the estimation of signal parameters such as the angles or the delays of arrival. The paper examines two-dimensional (2D) joint angles and delays of arrival estimation using channel state information when the OFDM transmit symbol undergoes multipath fading and is received through multiple coherent signals using a uniform linear antenna array. Parameter estimation from coherent signals requires spatio-frequential smoothing receive preprocessing before the application of 2D subspace methods. The paper studies the estimation performance of such high-resolution algorithms combined with the recent method of correlation vectors subspace for improved parameter covariance matrix estimation. Different variants of the correlation vectors subspace method are considered. Simulation results show that the root mean square error for different number of snapshots and for low signal-to-noise ratio is reduced over the case where parameter estimation is performed without the correlation vectors subspace technique.