Aircraft Detection for HR SAR Images in Non-homogeneous Background Using GGMD-Based Modeling

HU Hao; HUANG Lanqing; YU Wenxian

doi:10.1049/cje.2019.08.010

Volume 28 Issue 6

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Article Navigation > Chinese Journal of Electronics > 2019 > 28(6): 1271-1280

HU Hao, HUANG Lanqing, YU Wenxian, “Aircraft Detection for HR SAR Images in Non-homogeneous Background Using GGMD-Based Modeling,” Chinese Journal of Electronics, vol. 28, no. 6, pp. 1271-1280, 2019, doi: 10.1049/cje.2019.08.010

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HU Hao, HUANG Lanqing, YU Wenxian, “Aircraft Detection for HR SAR Images in Non-homogeneous Background Using GGMD-Based Modeling,” Chinese Journal of Electronics, vol. 28, no. 6, pp. 1271-1280, 2019, doi: 10.1049/cje.2019.08.010

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Aircraft Detection for HR SAR Images in Non-homogeneous Background Using GGMD-Based Modeling

doi: 10.1049/cje.2019.08.010

Shanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai 200240, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61331015).

Received Date: 2018-06-14
Rev Recd Date: 2018-12-04
Publish Date: 2019-11-10

Abstract

Abstract

In the problem of aircraft detection for High resolution (HR) Synthetic aperture radar (SAR) images, the background areas commonly contain multiple land cover types, such as runways and grassland. The conventional Constant false alarm rate (CFAR) detection in these non-homogeneous backgrounds with homogeneous assumption leads to unreliable detection results. This paper constructs a one-stage detection method based on the Generalized gamma mixture distribution (GGMD), which is regarded as a competitive and applicable model for combining the advantages of the Generalized gamma distribution (GGD) and the Finite mixture model (FMM). In order to evaluate the availability of the proposed algorithm, HR SAR images for aircraft detection from different product types and with various resolutions are examined. Compared with the CFAR algorithms based on the Gamma distribution, the GGD, and the gamma mixture distribution, the proposed algorithm demonstrates its availability and effectiveness for aircraft detection in HR SAR images in non-homogeneous background.

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References(29)

References

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