Low-complexity estimation of signal parameters via rotational invariance techniques algorithm for mixed far-field and near-field cyclostationary sources localisation

Abstract

In this study, the authors propose an efficient third-order cyclic moment-based estimation of signal parameters via rotational invariance techniques algorithm to cope with the mixed far-field and near-field cyclostationary sources localisation problem. The key point is that the auto-pairing parameters of near-field bearing and range is realised by estimating the unique non-singular matrix between the signal subspace and the matrix of direction vectors. This algorithm firstly constructs two special third-order cyclic moment matrices, in which the rotational factor is the function of the direction-of-arrival (DOA) and range of mixed far-field and near-field sources. By implementing the singular value decomposition and the high-resolution multiple signal classification spectral search, the authors estimate the azimuth DOAs for all the incoming sources. Then, the authors perform the estimation of the unique non-singular matrix between the signal subspace and the matrix of direction vectors. Finally, the range of near-field sources is determined from the obtained rotational factor. The proposed algorithm is computationally more efficient than the previous works, and it avoids pairing parameters. Computer simulations are carried out to demonstrate the performance of the proposed algorithm.