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Dual super-systolic core for real-time reconstructive algorithms of high-resolution radar/SAR imaging systems.

Atoche AC, Castillo JV - Sensors (Basel) (2012)

Bottom Line: The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms.As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene.We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechatronics, Autonomous University of Yucatan, Merida, Yucatan, Mexico. acastill@uady.mx

ABSTRACT
A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode.

No MeSH data available.


Related in: MedlinePlus

Implementation results for the first observation scenario: (SNR μ = 10 dB): (a) Original tested scene; (b) degraded scene image formed applying the MSF method; (c) image reconstructed applying the CLS algorithm; (d) image reconstructed applying the WCLS algorithm.
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f7-sensors-12-02539: Implementation results for the first observation scenario: (SNR μ = 10 dB): (a) Original tested scene; (b) degraded scene image formed applying the MSF method; (c) image reconstructed applying the CLS algorithm; (d) image reconstructed applying the WCLS algorithm.

Mentions: Next, the qualitative results are presented in Figures 7 and 8, with two different real-world high-resolution scenes. Figure 7(a,b) show the original test scene images. Figures 7(b) and 8(b) present the noised low-resolution (degraded) scene images formed with the conventional MSF algorithm. Figures 7(c) and 8(c) present the scene images reconstructed with the CLS-regularized algorithm. Figures 7(d) and 8(d) present the scene images reconstructed employing the WCLS-regularized algorithm.


Dual super-systolic core for real-time reconstructive algorithms of high-resolution radar/SAR imaging systems.

Atoche AC, Castillo JV - Sensors (Basel) (2012)

Implementation results for the first observation scenario: (SNR μ = 10 dB): (a) Original tested scene; (b) degraded scene image formed applying the MSF method; (c) image reconstructed applying the CLS algorithm; (d) image reconstructed applying the WCLS algorithm.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376574&req=5

f7-sensors-12-02539: Implementation results for the first observation scenario: (SNR μ = 10 dB): (a) Original tested scene; (b) degraded scene image formed applying the MSF method; (c) image reconstructed applying the CLS algorithm; (d) image reconstructed applying the WCLS algorithm.
Mentions: Next, the qualitative results are presented in Figures 7 and 8, with two different real-world high-resolution scenes. Figure 7(a,b) show the original test scene images. Figures 7(b) and 8(b) present the noised low-resolution (degraded) scene images formed with the conventional MSF algorithm. Figures 7(c) and 8(c) present the scene images reconstructed with the CLS-regularized algorithm. Figures 7(d) and 8(d) present the scene images reconstructed employing the WCLS-regularized algorithm.

Bottom Line: The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms.As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene.We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechatronics, Autonomous University of Yucatan, Merida, Yucatan, Mexico. acastill@uady.mx

ABSTRACT
A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode.

No MeSH data available.


Related in: MedlinePlus