SAR platform positioning method based on improved Gauss–Newton–genetic hybrid algorithm

The traditional synthetic aperture radar (SAR) platform positioning methods based on the range-Doppler domain data, velocity and altitude information of the platform exist a large approximation error, which will not satisfy the requirement of accurate navigation. Additionally, the traditional positioning methods for solving non- linear equationsare challenging due to the risk of falling into local optimal solution. In order to solve these problems, a new robust SAR platform positioning method based on the improved Gauss–Newton–genetic hybrid (GNGH) algorithm is proposed in this study. First, the position information of multi-feature points in geographic and imaging coordinate systemsis acquired by adopting the image matching. Furthermore, the coordinate transformation is introduced to realise the uniform of feature point coordinates between the different coordinate systems. Finally, the accurate position of the platform is calculated through introducing GNGH algorithm to solve the non- linear equationsconstructed by the corresponding slant rangeinformation. So the trajectory deviation can be corrected effectively. Moreover, the proposed method can reduce the computation load and positioning error dramatically. The effectiveness of the proposed approach is confirmed and demonstrated via simulation and experimental results.