基于復(fù)高斯模型的樣本缺失窄帶雷達(dá)信號重構(gòu)算法
doi: 10.11999/JEIT141041
基金項(xiàng)目:
國家自然科學(xué)基金(61271024, 61201296, 61322103)和全國優(yōu)秀博士學(xué)位論文作者專項(xiàng)資金(FANEDD-201156)資助課題
Reconstruction Method for Narrow-band Radar Returns withMissing Samples Based on Complex Gaussian Model
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摘要: 該文提出一種針對窄帶雷達(dá)信號存在樣本缺失情況下的信號重構(gòu)算法。由于窄帶雷達(dá)體制下，目標(biāo)回波近似服從復(fù)高斯分布。在這一前提下，首先建立描述樣本缺失觀測信號與未知完整信號間關(guān)系的概率模型，然后根據(jù)貝葉斯準(zhǔn)則推導(dǎo)出在給定樣本缺失觀測信號條件下完整信號的后驗(yàn)分布，最后利用期望最大(Expectation Maximization, EM)算法得到模型中參數(shù)的最大似然估計(jì)，進(jìn)而得到完整信號的重構(gòu)。該方法的優(yōu)勢是只需利用樣本缺失觀測信號就可以重構(gòu)出未知的完整信號，除了復(fù)高斯分布的假設(shè)，不需要其他任何樣本信息和先驗(yàn)假設(shè)幫助參數(shù)學(xué)習(xí)?；趯?shí)測數(shù)據(jù)的實(shí)驗(yàn)結(jié)果和與現(xiàn)有算法的比較結(jié)果表明該方法能夠獲得較好的重構(gòu)性能。
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關(guān)鍵詞:
- 雷達(dá)信號處理 /
- 信號重構(gòu) /
- 復(fù)高斯分布 /
- 期望最大算法 /
- 窄帶雷達(dá)
Abstract: This paper proposes a new signal reconstruction method for the signals with missing samples obtained by narrow-band radar. For the narrow-band radar system, the target echoes can be assumed to follow the complex Gaussian distribution. Based on this precondition, first the probabilistic model between the observed signal with missing samples and the unknown complete signal is formulated. Then the posterior distribution of the complete signal is obtained via the Bayes' theorem. Finally, the maximum likelihood estimation of the model parameters is obtained with the Expectation Maximization (EM) algorithm and the reconstruction of the complete signal can be obtained. The advantage of the method is that the reconstruction of the complete signal only using the observed signal with missing samples based on the complex Gaussian distribution assumption, while no other signal and prior information are needed in the parameter learning process. Experiments based on the measured data and the comparation results with other state-of-the-art approaches show that the proposed method can achieve good reconstruction performance. -
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