Convolved Thinned Antenna Arrays for Close Target Separation

Radar systems' angular resolution depends on the available aperture size, which, for a practically limited aperture, impedes radar's ability to effectively resolve closely-spaced targets. A conventional approach to improving angular resolution would be to increase the number of antennas in a larger aperture, but this introduces power consumption, computational complexity, and area occupancy costs. A standard approach to reducing the number of antennas would be to sparsify the antenna array while maintaining the same aperture. These types of arrays are known as thinned arrays. Thinned arrays, however, have difficulty in resolving closely-spaced targets due to the manifestation of sidelobes causing the degradation of antenna directivity and/or gain. In this paper, we propose convolving two thinned arrays to attenuate sidelobes and improve closely-spaced target separation. The convolution of the two thinned arrays is analyzed and used to define atoms of a dictionary of a “virtual array”, allowing localization using the orthogonal matching pursuit (OMP) algorithm. In the simulated results, the proposed method is compared to two methods, one thinned array with twice the number of antennas as one of the thinned arrays used in convolution, and the average angle of arrival (AoA) estimates of each thinned array used in convolution. The results demonstrate the superiority of our proposed method in terms of improving closely-spaced target separation, even in the presence of an increased number of targets.