Joint frequency and 2-D angle estimation based on vector sensor array with sub-Nyquist temporal sampling

Abstract

A novel ESPRIT based algorithm is proposed to jointly estimate 2-dimensional direction-of-arrivals (2-D DOAs) and frequencies of the incoming superimposed complex sinusoidal signals using a sparse uniform linear array of electromagnetic vector-sensors. The proposed method is based on a matrix pencil pair of temporally displaced data sets that are collected from the electromagnetic vector sensor array, where the DOA and frequency estimates can be estimated unambiguously from the eigenvectors and eigenvalues of the matrix pencil even when the interelement spacing is more than half wavelength. A second algorithm is proposed to resolve the ambiguity problem in the frequency estimates when the temporal sampling rate is less than half of the Nyquist rate of the signal, i.e. the sampling rate is less than the maximum frequency of the signal. Simulation results support the proposed algorithms and show that the 2-D DOA and frequency estimates are asymptotically unbiased and have a low variance.