Sparse super-resolution imaging for airborne single channel forward-looking radar in expanded beam space via lp regularisation

An adaptive super-resolution imaging algorithm to enhance the performance of airborne single channel forward-looking radar is proposed. Multiple beams data to expand the processing space to enforce the sparsity of scatterers with respect to the antenna pattern was first utilised. Then, the imaging is converted into a problem of signal reconstruction with Lp-norm regularisation, and the regularisation parameter is data driven. Simulations are given to verify the effectiveness of the algorithm.