Imaging moving objects from multiply scattered waves and multiple sensors

Miranda, A. Cárdenas; Cheney, Margaret

doi:10.1088/0266-5611/29/5/054012

Inverse Problems

2013

DOI: 10.1088/0266-5611/29/5/054012

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Imaging moving objects from multiply scattered waves and multiple sensors

A. Cárdenas Miranda

Margaret Cheney

Abstract: 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 R… Show more

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Cited by 2 publications

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“…The paper by Borcea et al [11] develops two methods for estimating the motion of moving targets from data from a single moving antenna. The paper by Miranda and Cheney [12] develops methods for image formation from data collected by multiple fixed sensors in an environment that includes known multipath wave propagation.…”

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confidence: 99%

Radar imaging

Borden¹,

Cheney²

2013

Inverse Problems

Self Cite

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Because of their ability to operate without regard to day, night or weather conditions, radar systems are ubiquitous in remote sensing operations and are used in a wide variety of commercial and military applications. High resolution radar imaging, however, is a remote sensing subcategory that requires raw radar data to be collected over an artificially extended aperture that is much larger than the radar receiving antenna and processed to create a reflectivity image of a scene (typically by backprojection methods). These synthetic aperture radar imaging (SAR) methods have been in use for over 50 years and, while the methodology for simple radar imaging is quite mature, there are still many active research programs seeking to extend the quality of-and information obtained from-SAR images.At its heart, basic SAR imaging relies on a simplified model in which the electromagnetic waves propagate through vacuum from a known antenna location, and elements of the scene to be imaged are weakly scattering point-like elements whose relative positions are fixed during the data collection interval. When this model fails to accurately represent a particular imaging scenario, the usual result is image artifacts which confound follow-on interpretation. In the case of dynamic scenes, for example, we typically find that the locations of moving scene elements are often significantly displaced in the final image (relative to other scene components). This problem has been recognized for many decades but only recently have concerted research efforts been mounted to attack the issue.Limitations associated with the point scatterer model are not quite so apparent as in the moving target case. Here, the problem is more one of lost information than artifacts (though associated image artifacts are possible as well). Generally, the echo response from a target will be characterized by more than just its intensity and more careful models have lately included depolarization effects and frequency dependence in an effort to more completely characterize the behavior of the reconstructed SAR image.As with any computed image method there will, of course, be issues of effective and efficient algorithm design. Owing to the practical problems of collecting the radar data over a synthetic aperture (often measured by aircraft negotiating imprecise flight paths), the problem of SAR image reconstruction can be especially troublesome. Data registration errors, nonuniform sampling issues and wave propagation through complex media can adversely affect the reliability of the data by adding unknown phase errors which, in turn, reduce image resolution.In this special section, we have invited contributions from many of the leading researchers in the mathematics, physics and engineering of SAR imaging techniques. The papers collected here fall (roughly) into three categories.

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confidence: 99%

Radar imaging

Borden¹,

Cheney²

2013

Inverse Problems

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Resolution Analysis of Passive Synthetic Aperture Imaging of Fast Moving Objects

Borcea¹,

Garnier²,

Papanicolaou

et al. 2017

SIAM J. Imaging Sci.

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Imaging moving objects from multiply scattered waves and multiple sensors

Cited by 2 publications

References 9 publications

Radar imaging

Radar imaging

Resolution Analysis of Passive Synthetic Aperture Imaging of Fast Moving Objects

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