發(fā)布時間：2019-02-28 17:10

【摘要】：經驗模態(tài)分解算法在海雜波抑制和目標檢測方面具有應用潛力,但如何實現(xiàn)模態(tài)函數(shù)自動篩選和判別是算法的關鍵問題。通過分析模態(tài)函數(shù)諧波模型,提取其信號特征譜,選取檢測量實現(xiàn)目標自動檢測。首先,對雷達回波進行復數(shù)經驗模態(tài)分解;然后對得到的各個內模分量提取特征譜,并根據(jù)特征譜分布情況得到散布特征;最后基于散布特征在各個內模函數(shù)間的分布差異實現(xiàn)目標檢測。實測微波多普勒雷達數(shù)據(jù)處理結果表明,目標檢測結果和實際情況一致,且在一定的虛警率約束下檢測概率較傳統(tǒng)檢測算法有一定提高,為雷達海洋目標檢測提供了新方案。
[Abstract]:The empirical mode decomposition (EMD) algorithm has potential applications in sea clutter suppression and target detection, but how to automatically select and discriminate modal functions is the key problem of the algorithm. By analyzing the harmonic model of modal function, the characteristic spectrum of the signal is extracted, and the automatic detection of the target is realized by selecting the detection method. Firstly, the radar echo is decomposed by complex empirical mode, and then the characteristic spectrum is extracted from each internal model component, and the scattering feature is obtained according to the distribution of the characteristic spectrum. Finally, the target detection is realized based on the distribution difference among the internal model functions. The data processing results of the measured microwave Doppler radar show that the target detection results are consistent with the actual situation, and the detection probability under the constraint of a certain false alarm rate is higher than that of the traditional detection algorithm, which provides a new scheme for radar ocean target detection.
【作者單位】： 武漢大學電子信息學院;武漢大學地球空間信息技術協(xié)同創(chuàng)新中心;
【基金】：國家自然科學基金資助項目(41376182,41506201) 湖北省科技支撐計劃項目(2014BEC057) 國家重點研發(fā)計劃課題(2016YFC1400504) 海洋公益性行業(yè)科研專項重大項目(201205032)
【分類號】：TN957.51
，

本文編號：2431991