Assessment of Backprojection-based FMCW-SAR Image Restoration by Multiple Implementation of Kalman Filter

Acquisition of precise position and velocity information of GNSS-INS (Global Navigation Satellite System; Inertial Navigation System) sensors in obtaining SAR SLC (Single Look Complex) images from raw data using BPA (Backprojection Algorithm) was regarded decisive. Several studies on BPA were accompanied by Kalman Filter for sensor noise oppression, but often implemented once where insufficient information was given to determine whether the filtering was effectively applied. Multiple operation of Kalman Filter on GNSS-INS sensor was presented in order to assess the effective order of sensor noise calibration. FMCW (Frequency Modulated Continuous Wave)-SAR raw data was collected from twice airborne experiments whose GNSS-INS information was practically and repeatedly filtered via Kalman Filter. It was driven that the FMCW-SAR raw data with diverse path information could derive different order of Kalman Filter with optimum operation of BPA image restoration.

Automated summary

This study emphasizes the importance of acquiring precise position and velocity information from GNSS-INS sensors for obtaining SAR images through BPA. Multiple operations of Kalman Filter were conducted to assess the effective order of sensor noise calibration. Experimental results showed that different orders of Kalman Filter applied to FMCW-SAR raw data can achieve optimum BPA image restoration.