Attributed scattering centers for SAR ATR

Potter, Lee C.; Moses, Randolph L.

doi:10.1109/83.552098

Cited by 453 publications

(234 citation statements)

References 56 publications

(95 reference statements)

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“…1 As a result, 3-D reconstructions that incorporate and represent these features can provide strong indications to object shape.…”

Section: Wide-angle Radar Scatteringmentioning

confidence: 99%

“…1 scattering from processing of limited-angle apertures, along with noncoherent combinations of these points over wider angle apertures. A summary of the approach follows.…”

Section: Isolated Dominant Scattering Centersmentioning

confidence: 99%

“…However, for wide-percent-bandwidth measurements, and for wide-interrogation-angle widths in either ϕ or ψ, scattering can exhibit significant variation as a function of frequency and angle. 1 For such cases, traditional SAR image or volume reconstruction processing should be reconsidered. 2,3 In general, the backscattered response at location (x, y, z) on the object depends on frequency, angle, and polarization; this response can be thought of as an "antenna pattern" whose amplitude and phase depend on both angle (azimuth and elevation) and polarization.…”

Section: Wide-angle Radar Scatteringmentioning

confidence: 99%

“…This 3-D location is transformed from the local slant-plane coordinate system to a coordinate (x, y, z) in an absolute, targetcentered coordinate system, referred to as an "IFSAR point." Also, a test to determine whether |s 1 Equation 3 expresses the scattering matrix as a decomposition of these three canonical terms. The real parameters A, α, and θ, in particular, provide information about the physical characteristics of the dominant scattering mechanism in the resolution cell.…”

Section: Ifsar Processingmentioning

confidence: 99%

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Three-Dimensional Target Visualization From Wide-Angle IFSAR Data

Moses¹,

Adams²,

Hand³

et al. 2005

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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. About the Cover: Cover designs by the ERDC MSRC Scientific Visualization Center. For related stories, see page 3 (front cover) and page 15 (back cover).from the director . . .Bill Joy-the father of Berkeley UNIX, cofounder of Sun Microsystems, and major force behind Javarecently commented in an interview that technology has matured such that we are at an inflection point in how we shape the world around us and create our future in it.For the first time, we have begun to design things from the bottom up. For example, rather than shaping and planning and carving our way into new technology, we are designing new materials by piecing together individual atoms to create a desired set of properties.This is a powerful shift that many have already pointed out will fundamentally change the kinds of technologies we produce as artifacts of our culture. The computer is a key tool making this shift possible.Many of you are part of this trend. Some of you have even helped make it happen. Our job is to ensure that you continue to have the best tools available as you continue to shape our collective future. The most critical resource we provide is our staff; our computational engineers, visualization specialists, domain scientists, and support staff are the glue that joins supercomputers to the job of getting your work done. But the enabling piece that makes their work possible is the hardware itself.As a member of the U.S. Army Engineer Research and Development Center Major Shared Resource Center (ERDC MSRC) family, I'm sure you are aware of our most recent hardware installation. As this goes to press in early fall, we are installing a 4,176-processor Cray XT3. The XT3 is an Opteron-based machine capable of providing 21.7 TFLOPS of computational capability to the user community. This machine is a tremendous resource, and we anticipate that it will enable a host of new and expanded applications at a size and fidelity not previously attainable on Department of Defense (DoD) resources.We are also proud to announce that this machine is already setting world records. The ERDC XT3, named sapphire (read more about it inside this issue), is the most capable machine listed on the High Performance Computing (HPC) Challenge benchm...

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“…1 As a result, 3-D reconstructions that incorporate and represent these features can provide strong indications to object shape.…”

Section: Wide-angle Radar Scatteringmentioning

confidence: 99%

“…1 scattering from processing of limited-angle apertures, along with noncoherent combinations of these points over wider angle apertures. A summary of the approach follows.…”

Section: Isolated Dominant Scattering Centersmentioning

confidence: 99%

Section: Wide-angle Radar Scatteringmentioning

confidence: 99%

Section: Ifsar Processingmentioning

confidence: 99%

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Three-Dimensional Target Visualization From Wide-Angle IFSAR Data

Moses¹,

Adams²,

Hand³

et al. 2005

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“…The HRR profiles can be processed to extract one-dimensional scattering centers or time-frequency features [11,12]. A SAR target image can be well approximated as a sum of two-dimensional scattering centers which provide a concise, yet physically relevant description of the target [13][14][15]. But the conventional parametric scattering centers feature extraction is very complicate and very hard to solve.…”

Section: Introductionmentioning

confidence: 99%

Sar Target Classification Using Bayesian Compressive Sensing With Scattering Centers Features

Zhang¹,

Qin²,

Li³

2013

PIER

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Abstract-The emerging field of compressed sensing provides sparse reconstruction, which has demonstrated promising results in the areas of signal processing and pattern recognition. In this paper, a new approach for synthetic aperture radar (SAR) target classification is proposed based on Bayesian compressive sensing (BCS) with scattering centers features. Scattering centers features is extracted as a l 1 -norm sparse problem on the basis of SAR observation physical model, which can improve discrimination ability compared with original SAR image. Using an overcomplete dictionary constructed by training samples, BCS is utilized to design targets classifier. For target classification performance evaluation, the proposed method is compared with several state-of-art methods through experiments on Moving and Stationary Target Acquisition and Recognition (MSTAR) public release database. Experiment results illustrate the effectiveness and robustness of the proposed approach.

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RCS Diagnostic Imaging Using Parameter Extraction Technique of State Space Method

Huang

Liu

Zhou

et al. 2022

Preprint

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The signature extraction and processing are the key aspects of enhancing recognition ability for radar target characteristics. In this paper, to reveal the intrinsic property of the target and improve the accuracy of radar cross section(RCS), we proposed RCS diagnostic imaging technique, extracting the parameters of scattering center model by state space method(SSM), to analyze the signature of GTD-based returns. Comparison with estimating signal parameter via rotational invariance techniques(ESPRIT) method, reconstructing the RCS profile through original and recovery signal, and employing SSM to the PEC sphere simulation, both the signature of specular and creeping wave extraction, the validation of SSM completely achieved the diagnostic imaging by means of parameter extraction.

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Attributed scattering centers for SAR ATR

Cited by 453 publications

References 56 publications

Three-Dimensional Target Visualization From Wide-Angle IFSAR Data

Three-Dimensional Target Visualization From Wide-Angle IFSAR Data

Sar Target Classification Using Bayesian Compressive Sensing With Scattering Centers Features

RCS Diagnostic Imaging Using Parameter Extraction Technique of State Space Method

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