Challenges and Opportunities for Staggered SAR with Low Oversampling Factors

Abstract

Staggered synthetic aperture radar (SAR) faces the challenge that a high oversampling ratio is required to avoid degradation in image quality at the cost of increased range ambiguities and data rates. This paper suggested that the opportunities for low-oversampled staggered SAR arise from novel pulse repetition interval (PRI) variation and advanced signal processing. We proposed a stepwise PRI variation scheme that spreads the blind ranges more evenly and benefits the estimation of the missing information. We combined deramping, spectral estimation, and linear Bayesian estimator to improve the recovery accuracy of the blockage data. Quasi-stationary signals with slowly changing spectra are obtained after deramping. Then the linear Bayesian estimator with the estimated spectrum as the prior information is applied for blockage recovery. Simulation results have verified that the proposed method has better performance than existing methods due to its adaptation to ground scattering characteristics.