Azimuth signal reconstruction for hrws-sar from uniform resampling
Konferenz: AIIPCC 2021 - The Second International Conference on Artificial Intelligence, Information Processing and Cloud Computing
26.06.2021 - 28.06.2021 in Hangzhou, China
Tagungsband: AIIPCC 2021
Seiten: 5Sprache: EnglischTyp: PDF
Zhang, Hanqing; Wu, Lin; Li, Ning (Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng, China & College of Computer and Information Engineering, Henan University, Kaifeng, China)
Signal reconstruction is a key step in the azimuth multichannel high-resolution wide-swath synthetic aperture radar (HRWS-SAR) imaging algorithms. Krieger’s digital beam-forming (DBF) algorithm is currently one of the commonly used algorithms for processing HRWS-SAR data. However, this algorithm is only suitable for uniform space-time sampling and moderately non-uniform sampling. In the case of highly non-uniform sampling, the imaging performance of Krieger’s DBF algorithm will be seriously deteriorated. In this paper, a uniform resampling algorithm is presented to solve above problem. The proposed algorithm adopts modern sampling theory to reduce the approximate error. This algorithm consists of two key steps: 1. The given signal samples are projected onto a selected intermediate subspace, spanned by integer translations of a compactly supported kernel function. This process generates a sparse set of equations, which can be effectively solved by using a sparse equation solvers. 2. The results are projected onto the subspace where the sampled signal is known to reside. The orthogonal matching pursuit (OMP) algorithm is used to realize the second projection and reconstruction the signal effectively. Simulation results show that the newly proposed algorithm has a significant improvement in imaging performance than Krieger’s DBF algorithm.