本文選題：寬帶線性調(diào)頻信號　切入點：信號抑噪　出處：《電子科技大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：寬帶線性調(diào)頻信號在軍事、雷達及聲吶等范圍內(nèi)被普遍應(yīng)用。如何對雷達回波信息進行噪聲抑制已成為信號處理領(lǐng)域中的研究熱點。盡管在以前的幾十年里,關(guān)于信號的噪聲抑制理論和算法得到了一定的發(fā)展,然而大部分方法對寬帶線性調(diào)頻信號抑噪?yún)s已不再適用。本文主要針對寬帶線性調(diào)頻信號的特征及處理方法,從信號噪聲抑制方法的基礎(chǔ)上展開深入研究。從提高輸出信噪比、降低算法復(fù)雜度入手,研究不同類型的噪聲對寬帶線性調(diào)頻信號的影響,以及不同抑噪算法對寬帶線性調(diào)頻信號噪聲抑制的效果。同時,并通過大量仿真驗證了本文所提及抑噪方法的優(yōu)勢和有用性。本文研究的重點內(nèi)容和創(chuàng)新點如下:首先,研究分析不同噪聲對寬帶線性調(diào)頻信號的影響。雷達的距離分辨率可以采用非常窄的脈沖來顯著地提高,而采用較窄的脈沖會降低平均發(fā)射功率,因為它與接收機信噪比之間的關(guān)系很緊密,所以通常期望在增加脈寬的同時保持足夠的分辨率。使用脈沖壓縮方法將會使這種期望成為可能,脈沖壓縮雷達的抗干擾能力很強,而普通噪聲對其干擾效果有限。因而,本文先研究不同噪聲干擾對寬帶線性調(diào)頻信號的影響,仿真結(jié)果表明各種噪聲干擾效果不一。其次,研究基于小波變換的信號抑噪方法,從基于多分辨分析概念產(chǎn)生的小波分解與重構(gòu)抑噪,到從小波奇異性檢測理論而產(chǎn)生的小波變換模極大值抑噪,及小波變換閾值抑噪;同時闡述了基于稀疏分解的信號抑噪理論,并研究分析了貪婪匹配追蹤算法,同時結(jié)合小波抑噪,進一步研究基于稀疏的抑噪方法。仿真實驗結(jié)果表明:針對寬帶線性調(diào)頻信號噪聲的抑制,在抑噪效果方面,稀疏分解總體優(yōu)于小波變換;而在運算速度方面,小波明顯比稀疏分解占有優(yōu)勢。最后,深入研究了基于經(jīng)驗?zāi)B(tài)分解的三種抑噪算法,針對原模態(tài)相關(guān)法未考慮到噪聲分量中可能會含有有用信號的問題,給出了新模態(tài)相關(guān)小波抑噪算法,仿真實驗顯示新算法的抑噪效果明顯比原算法具有優(yōu)勢。然后將小波變換與稀疏表示相結(jié)合,給出了改進后的基于經(jīng)驗?zāi)B(tài)分解的抑噪算法,仿真結(jié)果驗證了該方法的有效性,信噪比并得到了一定的提高。
[Abstract]:Wideband linear frequency modulation (LFM) signals are widely used in military, radar and sonar fields. How to suppress the noise of radar echo information has become a research hotspot in the field of signal processing. The theory and algorithm of signal noise suppression have been developed, but most of the methods are no longer applicable to wideband LFM signals. This paper focuses on the characteristics and processing methods of wideband LFM signals. Based on the method of signal noise suppression, the effect of different types of noise on wideband LFM signal is studied by improving the output SNR and reducing the complexity of the algorithm. And the effect of different noise suppression algorithms on the noise suppression of wideband LFM signals. At the same time, the advantages and usefulness of the noise suppression methods mentioned in this paper are verified by a large number of simulations. The key contents and innovations of this paper are as follows: first, The influence of different noise on wideband LFM signal is studied. The range resolution of radar can be improved significantly by using very narrow pulse, but the average transmitting power can be reduced by using narrower pulse. Because it is closely related to the signal-to-noise ratio (SNR) of the receiver, it is usually expected to maintain sufficient resolution while increasing the pulse width. This expectation will be made possible by using the pulse compression method, and the anti-jamming capability of the pulse compression radar is very strong. The effect of ordinary noise on the interference is limited. Therefore, the influence of different noise on wideband LFM signal is studied in this paper, and the simulation results show that the noise jamming effect is different. Secondly, the signal noise suppression method based on wavelet transform is studied. From wavelet decomposition and reconstruction based on the concept of Multiresolution analysis to wavelet transform modulus maximum noise suppression and wavelet transform threshold noise suppression; At the same time, the theory of signal noise suppression based on sparse decomposition is expounded, and the greedy matching tracking algorithm is studied and analyzed. The simulation results show that for wideband LFM signal noise suppression, the sparse decomposition is better than wavelet transform in noise suppression effect, but in the aspect of computing speed, Wavelet is obviously superior to sparse decomposition. Finally, three noise suppression algorithms based on empirical mode decomposition are studied in depth. A new mode-dependent wavelet denoising algorithm is presented. The simulation results show that the new algorithm has obvious advantages over the original algorithm. Then, an improved denoising algorithm based on empirical mode decomposition is proposed by combining wavelet transform with sparse representation. The simulation results show that the method is effective and SNR is improved.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN911.4

【參考文獻】

相關(guān)期刊論文 前2條

1 李燕平;汪志強;肖yN;;LFM信號的卷積調(diào)制干擾仿真[J];電子信息對抗技術(shù);2011年04期

2 郭雪鋒;方立軍;馬駿;張焱;;寬帶線性調(diào)頻信號的性能檢測方法[J];雷達科學(xué)與技術(shù);2012年05期

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本文編號：1592751