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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

Dual SSA core of the RS-related estimator.
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f3-sensors-12-02539: Dual SSA core of the RS-related estimator.

Mentions: In Figure 3, the conceptualization of the fixed-point dual SSA core is depicted. From the analysis of Figure 3, one can deduce the dual SSA machine running in parallel, and then, the element by element Shur-Hadamar operation, for the implementation of the optimal reconstructive RS estimator of Equation (1). This SSA efficiently computes the complex SSP estimation of the RS algorithms. Notice that at this implementation stage, Figure 3 only describes the HW-level architecture at a coarse grain detail. Through this figure, one also can deduce how such complex matrix operators are working in order to perform optimal reconstructive RS estimator.


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

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

Dual SSA core of the RS-related estimator.
© Copyright Policy
Related In: Results  -  Collection

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

f3-sensors-12-02539: Dual SSA core of the RS-related estimator.
Mentions: In Figure 3, the conceptualization of the fixed-point dual SSA core is depicted. From the analysis of Figure 3, one can deduce the dual SSA machine running in parallel, and then, the element by element Shur-Hadamar operation, for the implementation of the optimal reconstructive RS estimator of Equation (1). This SSA efficiently computes the complex SSP estimation of the RS algorithms. Notice that at this implementation stage, Figure 3 only describes the HW-level architecture at a coarse grain detail. Through this figure, one also can deduce how such complex matrix operators are working in order to perform optimal reconstructive RS estimator.

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