Synthetic Aperture Radar (SAR) technology is capable to provide high resolution image data of earth surfaces from a moving vehicle. This causes large volumes of raw data. Many researchs were proposed about compressed radar imaging, which can reduce the sampling rate of the analog digital converter (ADC) on the receiver and eliminate the need of match filter on the radar receiver. Besides the advantages, there is a major problem that produces a large measurement matrix, which causes a very intensive matrix calculation. In this paper is studied a new approach to partial acquisition technique to reduce the amount of raw data using compressed sampling in both the azimuth and range and to reduce the computational load. The results showed that the reconstruction of SAR image using partial acquisition model has good resolution comparable to the conventional method (Range Doppler Algorithm). On a target of a ship, that represents a low level sparsity, a good reconstruction image could be achieved from a fewer number measurement. The method can speed up the computation time by a factor of 2.64 to 4.49 times faster than with a full acquisition matrix.
|Journal||IOP Conference Series: Earth and Environmental Science|
|Publication status||Published - 11 Feb 2017|
|Event||3rd International Symposium on LAPAN-IPB Satellite for Food Security and Environmental Monitoring 2016, LISAT-FSEM 2016 - Bogor, Indonesia|
Duration: 25 Oct 2016 → 26 Oct 2016