DOA estimation for periodically modulated sources

Abstract

This paper considers the problem of direction-of-arrival estimation for periodically modulated signals using one uniform linear array of sensors. By means of modulating the sources with periodic modulation sequences, we can form a series of linear equations relating the autocorrelation matrices of the received data and the outer products of the scaled steering vectors. Solving these linear equations yields a group of Hermitian matrices formed from the outer products of the scaled steering vectors. Then taking the eigendecomposition of these Hermitian matrices, we can obtain all the scaled steering vectors. By utilizing a special structure of the scaled steering vectors, we can find the directions of signals impinging on the array. We also examine the relation of the modulation sequences and the estimation performance, and a design of the modulation sequences to resist the effect of spatial noise is proposed. One merit of the proposed method is that it can be used in the scenarios of more sources than sensors. The simulation result also shows that it has the capacity to distinguish the closely spaced sources.