High-Squint SAR Data Generation and Processing with Validation on Real Data

Abstract

The squinted strip-map synthetic aperture radar (SAR) mode for fighter airborne radar provides more operational advantage than the side-looking mode. The high platform dynamics of the fighter plane and severe range-azimuth coupling for high squint scenario imposes more challenges compared to the side-looking mode for SAR image formation algorithm. Most of the SAR algorithms fail to provide reasonable image focusing performance with reasonable computational complexity in high-squint, high-resolution strip-map SAR mode. This paper presents the real-time hardware implementable version of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\omega$</tex> -k image formation algorithm with sensor-based motion compensation for linear frequency modulation (LFM) and de-chirp mode. This paper also presents the SAR raw data simulator for LFM and de-chirp mode, which considers the non-ideal platform trajectory. The proposed method is implemented on real-time hardware, validated on real SAR data till 70 degree squint angle, and provided better than 100 m geo-coding accuracy.