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海雜波AR譜多重分形特性及微弱目標檢測方法

范一飛,  羅豐,  李明,  胡沖,  陳帥霖

范一飛, 羅豐, 李明, 胡沖, 陳帥霖. 海雜波AR譜多重分形特性及微弱目標檢測方法[J]. 電子與信息學報, 2016, 38(2): 455-463. doi: 10.11999/JEIT150581
引用本文: 范一飛, 羅豐, 李明, 胡沖, 陳帥霖. 海雜波AR譜多重分形特性及微弱目標檢測方法[J]. 電子與信息學報, 2016, 38(2): 455-463. doi: 10.11999/JEIT150581
FAN Yifei, LUO Feng, LI Ming, HU Chong, CHEN Shuailin. The Multifractal Properties of AR Spectrum and Weak Target Detection in Sea Clutter Background[J]. Journal of Electronics & Information Technology, 2016, 38(2): 455-463. doi: 10.11999/JEIT150581
Citation: FAN Yifei, LUO Feng, LI Ming, HU Chong, CHEN Shuailin. The Multifractal Properties of AR Spectrum and Weak Target Detection in Sea Clutter Background[J]. Journal of Electronics & Information Technology, 2016, 38(2): 455-463. doi: 10.11999/JEIT150581

海雜波AR譜多重分形特性及微弱目標檢測方法

doi: 10.11999/JEIT150581
基金項目: 

國家部委基金(4010101030101)

The Multifractal Properties of AR Spectrum and Weak Target Detection in Sea Clutter Background

Funds: 

The National Ministries Fund (4010101030101)

  • 摘要: 該文研究了海雜波功率譜的多重分形特性。為了克服頻譜傅里葉分析的缺點，用現(xiàn)代譜估計的方法來計算海雜波的功率譜。AR模型是一個線性預測模型，它通過序列的自相關函數(shù)矩陣來估計功率譜，并且具有更精確的頻譜分辨率。該文主要分析基于AR譜估計的海雜波功率譜的多重分形特性，以及在微弱目標檢測中的應用。首先，以分數(shù)布朗運動(FBM)模型為例，證明其功率譜具有多重分形特性。其次，根據X波段雷達的實測海雜波數(shù)據，通過多重去趨勢分析法(MF-DFA)驗證了海雜波AR譜的多重分形特性。最后，分析了海雜波AR譜的廣義Hurst指數(shù)以及影響參數(shù)，并提出一種基于局部AR譜廣義Hurst指數(shù)的目標檢測方法。實驗結果表明，該種檢測方法具有海雜波背景下微弱目標檢測的能力。與現(xiàn)有的分形檢測方法和傳統(tǒng)的CFAR檢測方法對比，該算法在低信雜比情況下具有較好的檢測性能。
    Abstract: This paper focuses on the multifractal properties of sea clutter in power spectrum domain. To overcome the deficiencies of Fourier transform analysis, the power spectrum of the sea clutter is obtained by AutoRegressive (AR) spectrum estimation. The AR model is a linear predictive model, which estimates the power spectrum of sea clutter from its autocorrelation matrix and has a higher frequency resolution than Fourier analysis. This paper concentrates on analyzing the multifractal property of the power spectrum based on AR spectral estimation and its application to weak target detection. Firstly, Fractional Brownian Motion (FBM) is taken as an example to prove the multifractal property of the power spectrum. Then, real measured X-band data is used to verify the multifractal property of the AR spectrum of sea clutter by MultiFractal Detrended Fluctuation Analysis (MF-DFA) method. Finally, the generalized Hurst exponent of AR spectrum and its influence factors are analyzed, and a novel detection method based on local AR generalized Hurst exponent is proposed. The results show that the proposed method is effective for weak target detection in sea clutter background. Compared to the existing fractal method and the traditional CFAR method, the proposed method has a better detection performance in low SCR condition.
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出版歷程
  • 收稿日期:  2015-05-15
  • 修回日期:  2015-10-13
  • 刊出日期:  2016-02-19

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