The Fast Factorized Back-Projection Algorithm (FFBPA) can reconstruct images in low sampling rate in Local Polar Coordinates (LPC). However, massive 2 dimensional image interpolations are required in image fusion from different LPCs. Image fusion is much easier in Cartesian Coordinates (CC), whereas, the Nyquist sampling rate of images in CC is higher, resulting in decline in the efficiency. To solve this problem, a spectrum compressing method is proposed. By compressing in range-time domain and range-frequency domain, the azimuth spectrum is greatly compressed. The image quality of the proposed method is similar to that of Back-Projection Algorithm (BPA) and is superior to that FFBPA. This method can also be used in SAR of nonlinear track. In the end, the validity of this method is proved by spaceborne SAR simulation data of 0.1 m resolution and airborne SAR real data of 0.2 m resolution.
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