An Optimal Sparse Reconstruction Algorithm in Synthetic Aperture Interferometric Radiometer (SAIR)

Synthetic aperture interferometric radiometer (SAIR) requires lots of antennas, receivers, and correlators to accurately reconstruct the brightness temperature (BT) distribution of the scene. Aiming to reduce the complexity of the hardware requirements in SAIR system while maintaining the image quality, a new optimal sparse reconstruction method is developed in this paper. Different from the existing imaging methods, the proposed method constructs the optimal receiving array with a few elements by evaluating the mutual coherence and the array factor of the sensing matrix in SAIR system, so as to achieve high-quality reconstruction of the BT image. Numerical simulations and experiments demonstrate that the proposed method can reconstruct the BT image by solely using a few receivers with higher image fidelity than the competing methods.