LAUSR

Multi-channel receiving technique has been proved to be a promising approach for synthetic aperture radar (SAR) to achieve simultaneous high-resolution and wide-swath (HRWS) imaging. With the support of digital beamforming (DBF) technique, ambiguity-free signal can be reconstructed from the Doppler aliased data received by along-track channels with high fidelity. However, in practice, a key factor that affects the precision of spectrum reconstruction and deteriorates the quality of final image is the inevitable mismatch between receiving channels. Thus, channel calibration is recognized as a crucial step prior to DBF. In this paper, we propose a novel channel calibration algorithm for multi-channel HRWS-SAR system. Instead of using signal subspace projection or other matrix decomposition methods adopted in most of the existing HRWS-SAR channel calibration algorithms, it tries to find ambiguity-free “sample signal” to be used in the estimation of channel error directly from the original Doppler ambiguous data. We demonstrate that, by applying sub-aperture operation to the original data, unambiguous multi-channel signal corresponding to isolated ground scatterers can be extracted, and thereby can be utilized to accurately estimate and calibrate the azimuth-variant channel mismatch. Experimental results from a four-channel and a three-channel airborne SAR systems are employed to validate the effectiveness and robustness of the proposed algorithm in practical processing.