A 3-D near-field source localization algorithm based on higher-order statistics using a small antenna array is presented in this paper. To suppress Gaussian color noises of unknown autocorrelation matrix in received array data, a specific fourth-order cumulant matrix instead of autocorrelation matrix is formed and an ESPRIT-like shift-invariance technique is used to estimate the phase differences among the antennas and ranges from the sources to the antennas simultaneously. Then a closed-form source location estimate is given by the solution of a set of linear equations. The proposed algorithm imposes no geometric constraint on the antenna array. Simulation results are provided to demonstrate the effectiveness and feasibility of this method.
Waveshrink has been proven to be a powerful tool for the problem of signal extraction from noisy data. A key step of the procedure is the selection of the threshold parameter. Donoho and Johnstone propose of the threshold based on a SURE procedure for real signals. In this paper, we discuss the issue of threshold selection for complex signals in Waveshrink. We first review the threshold selection procedure based minimax thresholds and then propose to extend the use of SURE procedure for denoising complex signals with complex wavelet transforms. At last, an example is used to show that the extended SURE procedure is an effective method for denoising complex signals.