Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm. 相似文献
Synthetic aperture interferometric technique has wide applications in optics, radio astronomy and microwave remote sensing
areas. With the increasing demands of high resolution imaging observation, a new time-sharing sampling scheme of asynchronous
rotation scan is proposed to meet the technical challenge of achieving a large equivalent aperture and overcome the operating
barriers of space borne application. This configuration is basically composed by two asynchronously and concentrically rotating
antenna groups, whose revolving radii and speeds are different. The synthetic aperture system with asynchronous rotation scanning
scheme can effectively solve the trade-off problem of system complexity, and greatly simplify the system hardware at the cost
of sacrificing a certain time resolution. The basic rules and design methods of asynchronous rotation scan are investigated
The Gridding method is introduced to inverse the spiral sampling data for image reconstruction. The potential applications
of geostationary orbit (GEO) earth observation and solar polar orbit (SPO) plasma cloud observation are explored with numerical
simulations to validate the significance and feasibility of this new imaging configuration.
Supported by the National Natural Science Foundation of China (Grant No. 40574070, 40671121, 40701100 and 40801136) and the
National High-Tech Research Program of China (“863” Program) (Grant No. 2006AA12Z141) 相似文献