Subspace‐Based Method for Direction Finding of Multiple Partially Polarized Signals

Abstract

We investigate the problem of direction finding for multiple Partially polarized (PP) electromagnetic signals, each of which possesses two spatial degrees of freedom. We use a uniform linear array of L sensors, where each consists of two co-located single-polarized elements. By exploiting the array geometry and its shift invariance property, we construct a set of data correlation sequences using the array output and its conjugate to transform the problem of direction finding to that of the estimation of complex sinusoid frequencies. The rank-2 signal correlation matrices of the PP signals become real-valued amplitudes of complex sinusoids, and thus, the rank-2K signal subspace of the array output transforms to the rank-K signal subspace of the constructed correlation sequences. We show that only L=K+1 sensors are needed to resolve K PP signals by solving the problem of estimation of sinusoid frequencies using subspace-based methods. The proposed method is also applicable to the scenario, where both Completely polarized (CP) and PP signals coexist, without the need of any prior information on the degree of polarization of the signal.