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

Abstract

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resolution is limited by real aperture, which result in traditional synthetic aperture radar imaging methods no longer applicable.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.

Keywords

• radar imaging
• radar resolution
• signal reconstruction