Low-complexity joint DOA/TOA estimation algorithm for mobile location

Abstract

In this thesis, we present a low-complexity joint estimation algorithm of the direction of arrival (DOA) and time of arrival (TOA) for mobile location system, which is based on a multiple signal classification (MUSIC) algorithm. To reduce the computational overhead of conventional joint DOA/TOA estimation algorithms, the proposed approach employs two complexity reduction schemes: separation of the signal vector for individually extracting DOA/TOA and pseudo-spectrum computation with discrete Fourier transform (DFT). In addition, the loss of accuracy caused by the separation process is compensated by summing multiple pseudo-spectrums. Compared with the conventional two-dimensional (2-D) MUSIC algorithm, the proposed low-complexity algorithm not only substantially reduces the computational complexity but also provides better performance, especially in a low signal-to-noise ratio (SNR). The effectiveness of the proposed algorithm is verified by simulation results.