Joint DOA and Frequency Estimation With Sub-Nyquist Sampling in the Sparse Array System

Several array systems along with algorithms based on sub-Nyquist sampling techniques have been extensively studied. This letter is committed to the joint frequency and direction-of-arrival estimation of more sources than sensors in a subband by using sparse arrays with sub-Nyquist sampling. The newly defined block vectorization eliminates the interference from sub-Nyquist sampling. Based on this, a novel augmented sample covariance matrix method is proposed, which enhances the spatial degrees of freedom and increases the number of identifiable sources. Simulations show that the joint estimation can be realized at a lower sampling rate with fewer sensors at the expense of a degradation in estimation performance. Such an algorithm provides a tradeoff between the expensive resource of sensors and channels, and the estimation performance.