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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.


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MPSoC platform of RS algorithms via the HW/SW co-design paradigm.
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f1-sensors-12-02539: MPSoC platform of RS algorithms via the HW/SW co-design paradigm.

Mentions: The term remote sensing (RS) is used to describe the science of identifying, observing, and measuring an object without coming into direct contact with it. This process involves the detection and measurement of different wavelength radiations, reflected or emitted from distant objects or materials, by which they may be identified and categorized by class, type, substance, and spatial distribution. RS systems are thus made of sensors mounted on an aircraft or a spacecraft that gather information from the Earth’s surface. Synthetic Aperture Radar (SAR) is an array of active sensors, and it is widely used in remote sensing missions to achieve high-resolution Earth images. In recent years, several efforts have been directed towards the incorporation of high-performance computing (HPC) models to remote sensing missions. Moreover, advances in sensor technology are revolutionizing the way remotely sensed data are collected, managed, and analyzed. In particular, many current and future applications of remote sensing in earth science, space science, and soon in exploration science require real- or near-real-time processing capabilities. In Figure 1, a multi-sensor image acquisition and reconstructive processing system based on a MPSoC platform for the enhancement/reconstruction of RS algorithms via the HW/SW co-design paradigm is illustrated.


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

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

MPSoC platform of RS algorithms via the HW/SW co-design paradigm.
© Copyright Policy
Related In: Results  -  Collection

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

f1-sensors-12-02539: MPSoC platform of RS algorithms via the HW/SW co-design paradigm.
Mentions: The term remote sensing (RS) is used to describe the science of identifying, observing, and measuring an object without coming into direct contact with it. This process involves the detection and measurement of different wavelength radiations, reflected or emitted from distant objects or materials, by which they may be identified and categorized by class, type, substance, and spatial distribution. RS systems are thus made of sensors mounted on an aircraft or a spacecraft that gather information from the Earth’s surface. Synthetic Aperture Radar (SAR) is an array of active sensors, and it is widely used in remote sensing missions to achieve high-resolution Earth images. In recent years, several efforts have been directed towards the incorporation of high-performance computing (HPC) models to remote sensing missions. Moreover, advances in sensor technology are revolutionizing the way remotely sensed data are collected, managed, and analyzed. In particular, many current and future applications of remote sensing in earth science, space science, and soon in exploration science require real- or near-real-time processing capabilities. In Figure 1, a multi-sensor image acquisition and reconstructive processing system based on a MPSoC platform for the enhancement/reconstruction of RS algorithms via the HW/SW co-design paradigm is illustrated.

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