Matching Items (3)
Description
For synthetic aperture radar (SAR) image formation processing, the chirp scaling algorithm (CSA) has gained considerable attention mainly because of its excellent target focusing ability, optimized processing steps, and ease of implementation. In particular, unlike the range Doppler and range migration algorithms, the CSA is easy to implement since it does not require interpolation, and it can be used on both stripmap and spotlight SAR systems. Another transform that can be used to enhance the processing of SAR image formation is the fractional Fourier transform (FRFT). This transform has been recently introduced to the signal processing community, and it has shown many promising applications in the realm of SAR signal processing, specifically because of its close association to the Wigner distribution and ambiguity function. The objective of this work is to improve the application of the FRFT in order to enhance the implementation of the CSA for SAR processing. This will be achieved by processing real phase-history data from the RADARSAT-1 satellite, a multi-mode SAR platform operating in the C-band, providing imagery with resolution between 8 and 100 meters at incidence angles of 10 through 59 degrees. The phase-history data will be processed into imagery using the conventional chirp scaling algorithm. The results will then be compared using a new implementation of the CSA based on the use of the FRFT, combined with traditional SAR focusing techniques, to enhance the algorithm's focusing ability, thereby increasing the peak-to-sidelobe ratio of the focused targets. The FRFT can also be used to provide focusing enhancements at extended ranges.
ContributorsNorthrop, Judith (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multidimensional (MD) discrete Fourier transform (DFT) is a key kernel algorithm in many signal processing applications, such as radar imaging and medical imaging. Traditionally, a two-dimensional (2-D) DFT is computed using Row-Column (RC) decomposition, where one-dimensional (1-D) DFTs are computed along the rows followed by 1-D DFTs along the columns. However, architectures based on RC decomposition are not efficient for large input size data which have to be stored in external memories based Synchronous Dynamic RAM (SDRAM). In this dissertation, first an efficient architecture to implement 2-D DFT for large-sized input data is proposed. This architecture achieves very high throughput by exploiting the inherent parallelism due to a novel 2-D decomposition and by utilizing the row-wise burst access pattern of the SDRAM external memory. In addition, an automatic IP generator is provided for mapping this architecture onto a reconfigurable platform of Xilinx Virtex-5 devices. For a 2048x2048 input size, the proposed architecture is 1.96 times faster than RC decomposition based implementation under the same memory constraints, and also outperforms other existing implementations. While the proposed 2-D DFT IP can achieve high performance, its output is bit-reversed. For systems where the output is required to be in natural order, use of this DFT IP would result in timing overhead. To solve this problem, a new bandwidth-efficient MD DFT IP that is transpose-free and produces outputs in natural order is proposed. It is based on a novel decomposition algorithm that takes into account the output order, FPGA resources, and the characteristics of off-chip memory access. An IP generator is designed and integrated into an in-house FPGA development platform, AlgoFLEX, for easy verification and fast integration. The corresponding 2-D and 3-D DFT architectures are ported onto the BEE3 board and their performance measured and analyzed. The results shows that the architecture can maintain the maximum memory bandwidth throughout the whole procedure while avoiding matrix transpose operations used in most other MD DFT implementations. The proposed architecture has also been ported onto the Xilinx ML605 board. When clocked at 100 MHz, 2048x2048 images with complex single-precision can be processed in less than 27 ms. Finally, transpose-free imaging flows for range-Doppler algorithm (RDA) and chirp-scaling algorithm (CSA) in SAR imaging are proposed. The corresponding implementations take advantage of the memory access patterns designed for the MD DFT IP and have superior timing performance. The RDA and CSA flows are mapped onto a unified architecture which is implemented on an FPGA platform. When clocked at 100MHz, the RDA and CSA computations with data size 4096x4096 can be completed in 323ms and 162ms, respectively. This implementation outperforms existing SAR image accelerators based on FPGA and GPU.
ContributorsYu, Chi-Li (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Karam, Lina (Committee member) / Cao, Yu (Committee member) / Arizona State University (Publisher)
Created2012
Description
Water is one of, if not the most valuable natural resource but extremely challenging to manage. According to old research in the field, many Water Distribution Systems (WDSs) around the world lose above 40 percent of clean water pumped into the distribution system because of unfortune leaks before the water gets anywhere from the fresh water resources. By reducing the amount of water leaked, distribution system managers can reduce the amount of money, resources, and energy wasted on finding and repairing the leaks, and then producing and pumping water, increase system reliability and more easily satisfy present and future needs of all consumers. But having access to this information pre-amatively and sufficiently can be complex and time taking. For large companies like SRP who are moving tonnes of water from various water bodies around phoenix area, it is even more crucial to efficiently locate and characterize the leaks. And phoenix being a busy city, it is not easy to go start digging everywhere, whenever a loss in pressure is reported at the destination.
Keeping this in mind, non-invasive methods to geo-physically work on it needs attention. There is a lot of potential in this field of work to even help with environmental crisis as this helps in places where water theft is big and is conducted through leaks in the distribution system. Methods like Acoustic sensing and ground penetrating radars have shown good results, and the work done in this thesis helps us realise the limitations and extents to which they can be used in the phoenix are.
The concrete pipes used by SRP are would not be able to generate enough acoustic signals to be affectively picked up by a hydrophone at the opening, so the GPR would be helpful in finding the initial location of the leak, as the water around the leak would make the sand wet and hence show a clear difference on the GPR. After that the frequency spectrum can be checked around that point which would show difference from another where we know a leak is not present.
Keeping this in mind, non-invasive methods to geo-physically work on it needs attention. There is a lot of potential in this field of work to even help with environmental crisis as this helps in places where water theft is big and is conducted through leaks in the distribution system. Methods like Acoustic sensing and ground penetrating radars have shown good results, and the work done in this thesis helps us realise the limitations and extents to which they can be used in the phoenix are.
The concrete pipes used by SRP are would not be able to generate enough acoustic signals to be affectively picked up by a hydrophone at the opening, so the GPR would be helpful in finding the initial location of the leak, as the water around the leak would make the sand wet and hence show a clear difference on the GPR. After that the frequency spectrum can be checked around that point which would show difference from another where we know a leak is not present.
ContributorsSrivastava, Siddhant (Author) / Lee, Taewoo (Thesis advisor) / Kwan, Beomjin (Committee member) / Kim, Jeonglae (Committee member) / Arizona State University (Publisher)
Created2019