摘要
A synthetic aperture radar (SAR) raw signal simulation algorithm for extended scenes is presented. This algorithm is based on the SAR two-dimensional system transform function (STF). To cope with range-variant nature of SAR STF and increase the speed of this algorithms, new formulas for range-variant phase corrections in range-Doppler (RD) domain are developed. In this way, many azimuth lines can be simulated with the same SAR STF. It only needs two-dimensional fast Fourier transform code and complex multiplications. Comparing with time-domain simulation algorithm, it is very simple and thus efficient. Simulation results have shown that this algorithm is accurate and efficient. Key words synthetic aperture radar - raw signal simulation - system transform function CLC number TP 751. 1 Foundation item: Supported by the National Natural Science Foundation of China (40376051)Biography: Sun Jin-yao (1967-), female, Ph. D. candidate, research direction: SAR image simulation and 3D recover for SAR image.
A synthetic aperture radar (SAR) raw signal simulation algorithm for extended scenes is presented. This algorithm is based on the SAR two-dimensional system transform function (STF). To cope with range-variant nature of SAR STF and increase the speed of this algorithms, new formulas for range-variant phase corrections in range-Doppler (RD) domain are developed. In this way, many azimuth lines can be simulated with the same SAR STF. It only needs two-dimensional fast Fourier transform code and complex multiplications. Comparing with time-domain simulation algorithm, it is very simple and thus efficient. Simulation results have shown that this algorithm is accurate and efficient. Key words synthetic aperture radar - raw signal simulation - system transform function CLC number TP 751. 1 Foundation item: Supported by the National Natural Science Foundation of China (40376051)Biography: Sun Jin-yao (1967-), female, Ph. D. candidate, research direction: SAR image simulation and 3D recover for SAR image.
基金
SupportedbytheNationalNaturalScienceFoundationofChina(40 3760 51 )
