A PARTIAL ACQUISITION TECHNIQUE OF SAR SYSTEM USING COMPRESSIVE SAMPLING METHOD
Abstract
In line with the development of Synthetic Aperture Radar (SAR) technology, there is a serious problem when the SAR signal is acquired using high rate analog digital converter (ADC), that require large volumes data storage. The other problem on compressive sensing method,which frequently occurs, is a large measurement matrix that may cause intensive calculation. In this paper, a new approach was proposed, particularly on the partial acquisition technique of SAR system using compressive sampling method in both the azimuth and range direction. The main objectives of the study are to reduce the radar raw data by decreasing the sampling rate of ADC and to reduce the computational load by decreasing the dimension of the measurement matrix. The simulation results found that the reconstruction of SAR image using partial acquisition model has better resolution compared to the conventional method (Range Doppler Algorithm/RDA). 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 study concludes that the method may speed up the computation time by a factor 4.49 times faster than with a full acquisition matrix.
Keywords
Full Text:
PDFReferences
Arief R., Sudiana D., Ramli K., (2016), Compressed Synthetic Aperture Radar Imaging Based on Maxwell Equation. J Teknol 78:15–22. doi: 10.11113/ jt.v78.8922.
Arief R., Sudiana D., Ramli K., (2015), A Framework of Synthetic Aperture Radar Imaging Based on Iterative Reweighted Compressed Sensing. Int J Simul Syst Sci Technol 16:15.1-15.7.
Arief R., Sudiana D., Ramli K., (2013), Noise effects on compressed SAR raw data. In: Proceedings of the 34th Asian Conference on Remote Sensing (ACRS), 20 – 24 October 2013. Bali, Indonesia, SC02. 1053-1060.
Arief R., Sudiana D., Ramli K., (2017), A study of the partial acquisition technique to reduce the amount of SAR data. In: IOP Conference Series: Earth and Environmental Science, The 3rd International Symposium on LAPAN-IPB Satellite For Food Security and Environmental Monitoring 2016, 25–26 October 2016, Bogor, Indonesia. Bogor, Indonesia, 12100.
Attema E., Cafforio C., Gottwald M., et al, (2010), Flexible Dynamic Block Adaptive Quantization for Sentinel-1 SAR Missions. IEEE Geosci Remote Sens Lett 7:766–770.
Baraniuk R., Steeghs P., (2007), Compressive Radar Imaging. In: Proc. IEEE Radar Conf. pp 128–133.
Candes EJ, Recht B., (2009), Exact Matrix Completion via Convex Optimization. Found Comput Math 9:717. doi: 10. 1007/s10208-009-9045-5.
Candes EJ, Romberg J., (2005), L1-magic: Recovery of Sparse Signals via Convex Programming.
Candes EJ, Tao T., (2006), Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Trans Inf Theory 52:5406–5425.
Candes EJ, Wakin MB, (2008), An Introduction To Compressive Sampling. IEEE Signal Process Mag 25:21–30.
Cheney M., Borden B., (2009), Problems in synthetic-aperture radar imaging. Inverse Probl 25:123005.
Cumming IG, Wong FH, (2005), Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Artech House.
Curlander JC, McDonough RN, (1991), Synthetic Aperture Radar: Systems and Signal Processing. Wiley.
Donoho DL, (2006), Compressed sensing. IEEE Trans Inf Theory 52:1289–1306.
Herman MA, Strohmer T., (2009), High-Resolution Radar via Compressed Sensing. IEEE Trans Signal Process 57, n:2275–2284.
Kankaku Y., Osawa Y., Suzuki S., (2011), The Current Status and Brief Results of Engineering Model for PALSAR-2 onboard ALOS-2. In: Proceedings of the 28th ISTS (International Symposium on Space Technology and Science), Okinawa, Japan, June 5-12, 2011. Okinawa, 2011-NaN-18.
Kwok R., Johnson W., (1989),Block adaptive quantization of Magellan SAR data. IEEE Trans Geosci Remote Sens 27:
Liu D., Boufounos PT, (2011), High Resolution SAR Imaging Using Random Pulse Timing. In: Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS). 4091–4094.
Patel VM, Easley GR, Healy Jr DM, Chellappa R., (2010), Compressed Synthetic Aperture Radar. IEEE J Sel Top Signal
Refbacks
- There are currently no refbacks.