Deterministic Blind Identification of IIR Systems With Output-Switching Operations

In this paper, a deterministic blind identification approach is proposed for linear output-switching systems, which are modeled by multiple infinite impulse-response (IIR) dynamic functions. By adopting a new over-sampling strategy, the concerned single-input-single-output (SISO) output-switching system is equivalently transformed into a time-invariant multi- input-multi-output (MIMO) system. Further, by exploring the mutual relations among the multiple inputs, the time-invariant MIMO system model and subsequently the output-switching system model are identified uniquely up to a scalar constant using the proposed identification approach. Sufficient identifiability conditions are provided for output-switching systems and numerical simulations are carried out to validate the proposed approach.

[1]  Jitendra K. Tugnait,et al.  Linear prediction error method for blind identification of periodically time-varying channels , 2002, IEEE Trans. Signal Process..

[2]  Philippe Loubaton,et al.  A subspace algorithm for certain blind identification problems , 1997, IEEE Trans. Inf. Theory.

[3]  Eric Moulines,et al.  Subspace methods for the blind identification of multichannel FIR filters , 1995, IEEE Trans. Signal Process..

[4]  Cishen Zhang,et al.  A New Deterministic Identification Approach to Hammerstein Systems , 2014, IEEE Transactions on Signal Processing.

[5]  Philippe Loubaton,et al.  On blind multiuser forward link channel estimation by the subspace method: identifiability results , 2000, IEEE Trans. Signal Process..

[6]  Andrew Kopeikin,et al.  Dynamic Mission Planning for Communication Control in Multiple Unmanned Aircraft Teams , 2013 .

[7]  Er-Wei Bai.  An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems , 1998, Autom..

[8]  Jitendra K. Tugnait,et al.  Blind identification of time-varying channels using multistep linear predictors , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Georgios B. Giannakis,et al.  Subspace methods for blind estimation of time-varying FIR channels , 1997, IEEE Trans. Signal Process..

[10]  Benoît Champagne,et al.  A Subspace Method for the Blind Identification of Multiple Time-Varying FIR Channels , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[11]  Philippe Loubaton,et al.  MIMO channel blind identification in the presence of spatially correlated noise , 2002, IEEE Trans. Signal Process..

[12]  T. Kailath,et al.  A least-squares approach to blind channel identification , 1995, IEEE Trans. Signal Process..

[13]  A. Gorokhov,et al.  Subspace-based techniques for blind separation of convolutive mixtures with temporally correlated sources , 1997 .

[14]  P. P. Vaidyanathan,et al.  Signal Processing and Optimization for Transceiver Systems , 2010 .

[15]  Hui Liu,et al.  Deterministic approaches for blind equalization of time-varying channels with antenna arrays , 1998, IEEE Trans. Signal Process..

[16]  J. Prasad,et al.  Development and Flight Test Evaluations of an Autonomous Obstacle Avoidance System for a Rotary-Wing UAV , 2013 .

[17]  Jitendra K. Tugnait,et al.  Time-Varying Channel Estimation Using Two-Dimensional Channel Orthogonalization and Superimposed Training , 2012, IEEE Transactions on Signal Processing.

[18]  Giacinto Gelli,et al.  Two-stage interference-resistant adaptive periodically time-varying CMA blind equalization , 2002, IEEE Trans. Signal Process..

[19]  Giacinto Gelli,et al.  Blind FSR-LPTV equalization and interference rejection , 2003, IEEE Trans. Commun..

[20]  S. Liberty,et al.  Linear Systems , 2010, Scientific Parallel Computing.

[21]  Cishen Zhang,et al.  Blind identification of non-minimum phase ARMA systems , 2013, Autom..

[22]  Fei Yuan.  On the periodicity of network functions of periodically switched linear and nonlinear circuits , 2000, 2000 Canadian Conference on Electrical and Computer Engineering. Conference Proceedings. Navigating to a New Era (Cat. No.00TH8492).

[23]  Lang Tong,et al.  Joint order detection and blind channel estimation by least squares smoothing , 1999, IEEE Trans. Signal Process..

[24]  Georgios B. Giannakis,et al.  Basis expansion models and diversity techniques for blind identification and equalization of time-varying channels , 1998, Proc. IEEE.

[25]  Tamal Bose,et al.  Blind Adaptive Equalization of MIMO Systems: New Recursive Algorithms and Convergence Analysis , 2010, IEEE Transactions on Circuits and Systems I: Regular Papers.

[26]  Nan Xiao,et al.  Stabilization of Markov jump linear systems using quantized state feedback , 2010, Autom..

[27]  Tongwen Chen,et al.  Representations of linear periodically time-varying and multirate systems , 2002, IEEE Trans. Signal Process..