A Vehicle-mounted SAR Motion Compensation Algorithm Based on Inertial Data

To address the issues of the difficulty in ensuring the ideal motion trajectory of the platform due to the flexible vehicle movement and the image defocusing caused by road turbulence, a motion compensation (MOCO) algorithm for vehicle-mounted synthetic aperture radar (SAR) based on inertial data is proposed in this paper, so as to realize the environment perception for unmanned driving based on vehicle-mounted millimeter wave SAR imaging. Firstly, high precision inertial navigation system (INS) is used to obtain the motion information of the platform, and the accuracy of INS is analyzed. Secondly, a geometric model of vehicle-mounted SAR motion error is established to analyze the instantaneous slant distance error. Due to the introduction of high-order space-time error, the image quality is affected, therefore, an accurate two-step MOCO algorithm is proposed to eliminate the space-time error and focusing on the target area is completed. Then, verifications are carried out by means of the simulation and the actual measurement, and the effectiveness of the algorithm is further proved from a quantitative perspective by introducing three quality evaluation indicators, such as impulse response width, peak sidelobe ratio and integrated sidelobe ratio. Finally, the experimental results show that the proposed MOCO algorithm can effectively process the vehicle-mounted, non-ideal trajectory SAR signal and obtain excellent imaging effect.