A Minimum-Energy-Based Algorithm for Multichannel Reconstruction - Sun, Liwei; Yu, Ze; Li, Chun-Sheng (IEEE geoscience and remote sensing letters, 2022)
For the azimuth multichannel synthetic aperture radar (SAR), nonuniform sampling is common since the pulse-repetition frequency cannot be selected arbitrarily, which leads to the contradiction between ambiguity and noise suppression in the azimuth signal reconstruction. This letter constructs a novel multichannel signal model by taking the coherence among different Doppler bins into account and proposes a minimum-energy-based multichannel reconstruction algorithm, which can obtain the unambiguous signal spectrum without increasing noise in the nonuniform sampling cases. By comparing the simulation results formed by digital beamforming (DBF), improved DBF (IDBF), and space-time adaptive processing (STAP) algorithms, the proposed algorithm shows better performance in balancing ambiguity and noise.