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

Abstract

In this paper, 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 pseudospectrum 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.Index Terms -Mobile location, direction of arrival (DOA), time of arrival (TOA), multiple signal classification (MUSIC)

Joint estimation of DOA and TOA for MB‐OFDM UWB signals based on frequency‐domain processing

“…For a two‐receiver case [27], a low‐complexity successive multiple signal classification (MUSIC) algorithm to estimate simultaneously the time delays from two antennas was developed, implicitly overcoming the pairing issue. However, the signal model in [28] neglects the phase difference that is caused by the array geometry. The comparison of the delay matrices associated with antenna 1 and antenna 2 indicates that the phase differences between the two antennas, which are caused by the time difference of arrival (TDOA) of all incident paths, are zero in the first row; however, the phase differences of all incident paths are maintained in the other rows of the delay matrices.…”

“…The comparison of the delay matrices associated with antenna 1 and antenna 2 indicates that the phase differences between the two antennas, which are caused by the time difference of arrival (TDOA) of all incident paths, are zero in the first row; however, the phase differences of all incident paths are maintained in the other rows of the delay matrices. Therefore, the signal model in [28] cannot be used to estimate the DOA of a signal source directly as it does not present correct phase differences of the two‐element linear array as the uniform linear array signal models in [29]. In the above methods, TOA errors strongly affect the accuracy of the DOA that is obtained using the JTDE scheme.…”

“…In the above methods, TOA errors strongly affect the accuracy of the DOA that is obtained using the JTDE scheme. In [28], a 2D space‐frequency model for narrow/wide band signals is considered and a low‐complexity joint DOA/TOA estimation based on MUSIC algorithm is proposed.…”

3D positioning scheme exploiting nano-scale IR-UWB orthogonal pulses

“…Based on the hybrid scheme, the 3D positioning system with mutually orthogonal nano-scale IR-UWB signals and cross array antenna is proposed. Specifically, the proposed scheme uses nano-scale IR-UWB signals providing fine time resolution and the 2D MUSIC algorithm for estimating the TOA and the AOA simultaneously [ 7 ]. In the proposed scheme, elevation angle ( ø ), azimuth angle ( θ ), and distance ( d ) between MS and BS are estimated through cross array antennas and positioning algorithm.…”

“…The discrete measurement data of Equation 3 can be obtained by sampling at L equally spaced frequencies, and it is given as follows [ 7 ]:…”