Probability density function of image tails interference in the detection of moving objects: generalized Rice's representation

Cheng-Youn Lu; Harrison E. Rowe

doi:10.1117/12.226817

17 November 1995 Probability density function of image tails interference in the detection of moving objects: generalized Rice's representation

Cheng-Youn Lu, Harrison E. Rowe

Author Affiliations +

Proceedings Volume 2587, Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing; (1995) https://doi.org/10.1117/12.226817
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

Passive radio wave remote sensing of a moving object by multiple individual sensors has been studied. A time-varying matched (TVM) filter bank has been suggested for the target reconstruction and detection. The TVM filter tuned to the target velocity compensates the target motion, maximizes SNR, and enhances the target image. In contrast, mis-tuned TVM filters yield blurred target images. In the multi-target case overlapped blurred image tails may interfere with the target recognition process, and cause target detection false alarm. In this work we study the statistics of the interference due to the randomly overlapped target image tails. Inspired by S. O. Rice's early work on shot noise statistics, assuming a uniform-Poisson distribution of target velocity-position, we present the probability density function (PDF), a generalized representation of Rice's integral, of the image tail interference. We evaluate this generalized Rice's integral. In an example we present the numerical results of the integral for the intermediate target density case.

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Cheng-Youn Lu and Harrison E. Rowe "Probability density function of image tails interference in the detection of moving objects: generalized Rice's representation", Proc. SPIE 2587, Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, (17 November 1995); https://doi.org/10.1117/12.226817

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KEYWORDS

Image filtering

Target detection

Image enhancement

Sensors

Signal to noise ratio

Antennas

Convolution

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