Super‐resolution forward‐looking imaging method for manoeuvering platform with optimised dictionary and extended sparsity adaptive matching pursuit

Abstract

In forward-looking imaging, left-right Doppler is ambiguous and cross-range resolution is limited by real aperture, which result in traditional synthetic aperture radar imaging methods no longer applicable. Besides, the impact of three-dimensional acceleration on an over-complete dictionary matrix and sparse reconstruction kernel is not considered in conventional super-resolution forward-looking imaging methods. To solve these problems, a super-resolution forward-looking imaging method for manoeuvering platforms is proposed. First, the range walk caused by forward-looking geometry and higher-order phase introduced by three-dimensional acceleration are eliminated by compensating a pre-processing function. Subsequently, according to beam steering-based geometry and linear regression model, the over-complete dictionary matrix is optimised to more accurately describe the complicated forward-looking geometry with curved trajectory. Finally, sparsity adaptive matching pursuit kernel with an improved halting condition is adopted to reconstruct the forward-looking scene. The proposed method is supported by point target simulation and surface target simulation.