On blind signal copy for polynomial phase signals

quency, the demodulated and sampled received signal can be modeled by, The problem of separating and estimating signals received by an array whose array manifold has an unknown structural form is usually referred to as the blind N X jÁ (t ) n k signal copy problem. In this paper we consider the x(t ) = a e +n(t ) = As(t ) +n(t ) (2) k n k k k blind signal copy problem for polynomial phase sign=1 nals. By deriving the Cramer Rao bound we evaluwhere a is the array manifold corresponding to the n ate the optimal performance achievable by any unbin-th source, and A is the M £N matrix consisting of ased estimator. To gain additional insight into this array manifold vectors. We assume that fn (t);m = m problem we compare the CRB to the bound for the 1; ¢ ¢ ¢ ;Mg is a white zero mean complex circular Gauscase where the functional form of the array manifold sian random process with variance ́, and noise samples is known. We derive a computationally e±cient apat di®erent sensors are uncorrelated with each other. proximate Maximum-Likelihood (ML) algorithm and The identi ̄ability of A is discussed in [1]. A can be at compare its performance with the bound. best identi ̄ed up to permutation and complex scaling of its columns. Therefore, we can assume without loss P