Blind Identification of SIMO Systems and Simultaneous Estimation of Multiple Time Delays From HOS-Based Inverse Filter Criteria

作者：Chong‐Yung Chi, Cheng‐Yi Chen, Chieh‐Hung Chen, Cui Feng, Chun-Hsien Peng · 发表于：IEEE Transactions on Signal Processing · 年份：2004 · DOI：10.1109/tsp.2004.834219 · 被引用次数：10 · 研究领域：Blind Source Separation Techniques、Speech and Audio Processing、Advanced Adaptive Filtering Techniques

Higher order statistics-based inverse filter criteria (IFC) have been effectively used for blind equalization of single-input multiple-output (SIMO) systems. Recently, Chi and Chen reported a relationship between the unknown SIMO system and the optimum equalizer designed by the IFC for finite signal-to-noise ratio (SNR). In this paper, based on this relationship, an iterative fast Fourier transform (FFT)-based nonparametric blind system identification (BSI) algorithm and an FFT-based multiple-time-delay estimation (MTDE) algorithm are proposed with a given set of non-Gaussian measurements. The proposed BSI algorithm allows the unknown SIMO system to have common subchannel zeros, and its performance (estimation accuracy) is superior to that of the conventional IFC-based methods. The proposed MTDE algorithm can simultaneously estimate all the (P-1) time delays (with respect to a reference sensor) with space diversity of sensors exploited; therefore, its performance (estimation accuracy) is robust to the nonuniform distribution of SNRs of P /spl ges/ 2 sensors (due to channel fading). Some simulation results are presented to support the efficacy of the proposed BSI algorithm and MTDE algorithm.