SUBSPACE METHODS FOR THE BLIND IDENTIFICATION OF MULTICHANNEL FIR FILTERS

This paper addresses a problem arising in a context of digital communications: ii digital source is transmitted through a continuous channel (the propagation medium), and several measurements are performed at the receiver, either by means of several sensors, or by oversampling the received signal compared to the emission rate. Given only these observations, the baseband equivalents of the corresponding channels have to be recovered. In this contribution, an orthogonality property betweeen ''signal'' and ''noise'' subspaces is exploited to build some quadratic form whose minimization yields the desired estimates up to a scale factor. This is in the same spirit as recent works by Tong ct al., but requires fewer computations. Numerical simulations demonstrate the performance of the proposed methods in a channel identification contest.