Sparse Array Antenna Signal Reconstruction using Compressive Sensing for Direction of Arrival Estimation

Direction of Arrival (DOA) estimation in radar applications depends on both the pattern quality and signal to noise ratio of a radar echo. To avoid inaccuracies in the DOA estimation precise knowledge is required for the main beam, and pattern sidelobes should be sufficiently small to suppress signals from other directions. In a sparse array the antenna beam pattern is degraded due to a broadened main beam with increased side lobes and the presence of grating lobes. Hence more energy is radiated into unwanted directions. It can be said that a dense array with defective elements is some sort of sparse array because the same disadvantages (high sidelobes, degraded antenna patterns) also occur when sparse arrays with element spacings > λ/2 are used. lt is however favorable to use sparse arrays since this can increase the resolution as the same amount of elements can be distributed over a larger antenna aperture. A literature study accompanied with Matlab simulations shows that compressive sensing techniques are able to reconstruct the antenna pattern of λ/2 spaced line array with failed elements. The signal of the M-element sparse line array which is reconstructed contains only 25% of the elements of its equivalent fully dense N-element λ/2 spaced array