Combined Adaptive GLRT-LTD against Sea Clutter

Liu Ming; Shui Peng-lang

doi:10.11999/JEIT150588

Volume 37 Issue 12

Jan. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(12): 2984-2990

Liu Ming, Shui Peng-lang. Combined Adaptive GLRT-LTD against Sea Clutter[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2984-2990. doi: 10.11999/JEIT150588

Citation:

Liu Ming, Shui Peng-lang. Combined Adaptive GLRT-LTD against Sea Clutter[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2984-2990. doi: 10.11999/JEIT150588

Liu Ming, Shui Peng-lang. Combined Adaptive GLRT-LTD against Sea Clutter[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2984-2990. doi: 10.11999/JEIT150588

Citation:

Liu Ming, Shui Peng-lang. Combined Adaptive GLRT-LTD against Sea Clutter[J]. Journal of Electronics & Information Technology, 2015, 37(12): 2984-2990. doi: 10.11999/JEIT150588

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Combined Adaptive GLRT-LTD against Sea Clutter

doi: 10.11999/JEIT150588

Liu Ming¹,
Shui Peng-lang¹

Funds:

The National Natural Science Foundation of China (61271295)

Received Date: 2015-05-18
Rev Recd Date: 2015-09-02
Publish Date: 2015-12-19

Abstract

Abstract

Long integration is often required to detect weak moving target in sea clutter. However, the Doppler frequency spread and amplitude fluctuation in long integration and limited reference cells resulting from spatial non-homogeneity of sea clutter make the traditional adaptive detector work badly. By observing that the Compound Gaussian Distribution (CGD) with Inverse Gamma (IG) texture gives a good fit to sea clutter and the instantaneous frequency is slowly varying, a combined adaptive detector, namely the Combined Adaptive Generalized Likelihood Ratio Test-Linear Threshold Detector (CA-GLRT-LTD), is proposed in the paper, which consists of the product of the maximal response of the adaptive GLRT-LTD in several continuous short integration intervals. Owing to the optimality of the GLRT-LTD for CG clutter with IG texture, the proposed detector obtains better performance than the Combined Adaptive Normalized Matched Filter (CANMF) detector.

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References(20)

References

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