Paper
29 August 2016 Detection of range-distributed targets in compound Gaussian clutter without secondary data
Yan-fei Zhang, Yu-mei Sun, Mei-chun Wang, Su Feng
Author Affiliations +
Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100330F (2016) https://doi.org/10.1117/12.2248753
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
Abstract
This paper consider the problem of detecting range-distributed targets using high resolution radar(HRR) in compound-Gaussian clutter without secondary data. To overcome the lack of training data, we first assume that clutter returns can be clustered into groups of cells sharing the same value of the noise power. Then an adaptive modified generalized likelihood ratio test (A-GLRT) detector is proposed by replacing the unknown parameters with their maximum likelihood estimations (MLEs). The proposed A-GLRT detector do not need secondary data and ensures constant false alarm rate (CFAR) property with respect to the unknown statistics of the clutter. Performances of this proposed detectors are assessed through Monte Carlo simulations and are shown to have better detection performance compared with existing similar modified generalized likelihood ratio test (MGLRT) detector.
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Yan-fei Zhang, Yu-mei Sun, Mei-chun Wang, and Su Feng "Detection of range-distributed targets in compound Gaussian clutter without secondary data", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100330F (29 August 2016); https://doi.org/10.1117/12.2248753
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KEYWORDS
Sensors

Target detection

Radar

Monte Carlo methods

Chromium

Data modeling

Palladium

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