Imaging radar performance analysis using product dark regions

Ann Marie Raynal; Douglas L. Bickel

doi:10.1117/12.2309372

4 May 2018 Imaging radar performance analysis using product dark regions

Ann Marie Raynal, Douglas L. Bickel

Proceedings Volume 10633, Radar Sensor Technology XXII; 1063310 (2018) https://doi.org/10.1117/12.2309372
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

Many types of dark regions occur naturally or artificially in Synthetic Aperture Radar (SAR) and Coherent Change Detection (CCD) products. Occluded regions in SAR imagery, known as shadows, are created when incident radar energy is obstructed by a target with height from illuminating resolution cells immediately behind the target in the ground plane. No return areas are also created from objects or terrain that produce little scattering in the direction of the receiver, such as still water or flat plates for monostatic systems. Depending on the size of the dark region, additive and multiplicative noise levels are commonly measured for SAR performance testing. However, techniques for radar performance testing of CCD using dark regions are not common in the literature. While dark regions in SAR imagery also produce dark regions in CCD products, additional dark regions in CCD may further arise from decorrelation of bright regions in SAR imagery due to clutter or terrain that has poor wide-sense stationarity (such as foliage in wind), man-made disturbances of the scene, or unintended artifacts introduced by the radar and image processing. By comparing dark regions in CCD imagery over multiple passes, one can identify unintended decorrelation introduced by poor radar performance rather than phenomenology. This paper addresses select dark region automated measurement techniques for the evaluation of radar performance during SAR and CCD field testing.

Citation Download Citation

Ann Marie Raynal and Douglas L. Bickel "Imaging radar performance analysis using product dark regions", Proc. SPIE 10633, Radar Sensor Technology XXII, 1063310 (4 May 2018); https://doi.org/10.1117/12.2309372

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KEYWORDS

Radar

Synthetic aperture radar

Signal to noise ratio

Image filtering

Filtering (signal processing)

Coherence (statistics)

Spatial coherence

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