【摘要】：從強(qiáng)噪聲中準(zhǔn)確提取單一正弦信號的頻率是通信系統(tǒng)、信號處理等領(lǐng)域一個(gè)非常重要的問題。目前,強(qiáng)噪聲背景下正弦信號頻率估計(jì)已經(jīng)成功應(yīng)用于雷達(dá)探測、語音信號處理、聲納地震、通信系統(tǒng)中的信號恢復(fù)、橋梁振動(dòng)檢測、生物醫(yī)學(xué)檢測以及電子通信技術(shù)等眾多領(lǐng)域,引起越來越多的學(xué)者的關(guān)注和重視。因此,對正弦信號頻率估計(jì)研究具有極其重要的理論意義和實(shí)際應(yīng)用價(jià)值。頻率是正弦信號最重要的參數(shù)和最本質(zhì)的特征,頻率估計(jì)研究是信號處理領(lǐng)域的一個(gè)經(jīng)典課題。本論文對幾類正弦信號頻率估計(jì)算法進(jìn)行研究,包括經(jīng)典的DFT算法、最大似然估計(jì)法、PHD算法、MC算法、TSA算法、Rife算法以及傅里葉系數(shù)插值迭代算法,分別在算法原理及計(jì)算量的基礎(chǔ)上比較了算法的性能,通過仿真實(shí)驗(yàn),得出頻率估計(jì)均方根誤差與信噪比之間的關(guān)系,并與頻率估計(jì)均方根誤差克拉美-羅下限做了比較。并且在分析總結(jié)各種算法的基礎(chǔ)上,提出了相應(yīng)的改進(jìn)算法。本文的主要研究工作及結(jié)論如下:1、提出了基于正弦信號LP性質(zhì)的分段自相關(guān)頻率估計(jì)新算法。該算法解決了兩步自相關(guān)頻率估計(jì)算法(TSA算法)估計(jì)性能和計(jì)算量不能兼顧的缺點(diǎn),在計(jì)算量較小的情況下逼近TSA2算法的性能,彌補(bǔ)了 TSA1改進(jìn)后帶來的計(jì)算量增加的問題。并對分段自相關(guān)算法進(jìn)行了仿真實(shí)驗(yàn),用結(jié)果分析其算法效果較好。2、提出了一種基于FFT的正弦信號頻率估計(jì)新算法。通過分析Rife算法和傅里葉系數(shù)迭代算法的性能可知,Rife算法計(jì)算簡單、精度不高,而傅里葉系數(shù)迭代算法需要兩次迭代之后才會(huì)到達(dá)精度要求,每次迭代的計(jì)算量大。結(jié)合Rife算法和傅里葉系數(shù)迭代算法這兩種算法的優(yōu)缺點(diǎn),本文新提出了一種改進(jìn)后的高精度頻率估計(jì)算法。并對此方法進(jìn)行了仿真實(shí)驗(yàn),結(jié)果分析其算法效果較好。
[Abstract]:The frequency of extracting a single sinusoidal signal from strong noise is a very important problem in the fields of communication system, signal processing and so on. At present, sinusoidal signal frequency estimation under the background of strong noise has been successfully applied to radar detection, speech signal processing, Sonar earthquake, signal recovery in communication system, bridge vibration detection, biomedical detection and electronic communication technology, which has attracted more and more scholars' attention and attention. Therefore, the study of sinusoidal signal frequency estimation is of great theoretical significance and practical application value. Frequency is the most important parameter and essential feature of sinusoidal signal. Frequency estimation is a classical topic in the field of signal processing. In this paper, several kinds of sinusoidal signal frequency estimation algorithms are studied, including classical DFT algorithm, maximum likelihood estimation method, PHD algorithm, MC algorithm, TSA algorithm, Rife algorithm and Fourier coefficient interpolation iterative algorithm. The performance of the algorithm is compared on the basis of algorithm principle and computation. Through simulation experiments, the relationship between root mean square error and signal to noise ratio of frequency estimation is obtained. It is compared with the root mean square error of frequency estimation. Based on the analysis and summary of various algorithms, the corresponding improved algorithms are proposed. The main research work and conclusions of this paper are as follows: 1. A new piecewise autocorrelation frequency estimation algorithm based on sinusoidal signal LP property is proposed. The algorithm solves the disadvantage that the performance and computation of two-step autocorrelation frequency estimation algorithm (TSA algorithm) can not be taken into account, and approaches the performance of TSA2 algorithm when the amount of computation is small, which makes up for the problem of increasing the amount of computation caused by the improvement of TSA1. The piecewise autocorrelation algorithm is simulated, and the results show that the algorithm is effective. 2, a new sinusoidal signal frequency estimation algorithm based on FFT is proposed. By analyzing the performance of Rife algorithm and Fourier coefficient iterative algorithm, it can be seen that the calculation of Rife algorithm is simple and the accuracy is not high, while the Fourier coefficient iterative algorithm needs two iterations to meet the accuracy requirements, and the computation of each iteration is large. Based on the advantages and disadvantages of Rife algorithm and Fourier coefficient iterative algorithm, an improved high precision frequency estimation algorithm is proposed in this paper. The simulation experiment of this method is carried out, and the results show that the algorithm is effective.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN911.23

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 謝勝;陳航;于平;林少興;;基于Quinn算法和相位差法的正弦波頻率估計(jì)綜合算法[J];信號處理;2011年05期

2 王天成;杜妍妍;陳娟;孫道霞;樂菁華;薛衛(wèi)娟;;電子胎心監(jiān)護(hù)正弦波型12例臨床分析[J];中華婦幼臨床醫(yī)學(xué)雜志(電子版);2010年06期

3 王宏偉;趙國慶;;正弦波頻率估計(jì)的改進(jìn)Rife算法[J];信號處理;2010年10期

4 朱磊;董亮;劉樹東;;基于Quinn算法與改進(jìn)的Rife算法的正弦信號頻率估計(jì)[J];大慶石油學(xué)院學(xué)報(bào);2010年01期

5 王宏偉;趙國慶;齊飛林;;一種實(shí)時(shí)精確的正弦波頻率估計(jì)算法[J];數(shù)據(jù)采集與處理;2009年02期

6 黃玉春;黃載祿;黃本雄;徐書華;;基于FFT滑動(dòng)平均極大似然法的正弦信號頻率估計(jì)[J];電子與信息學(xué)報(bào);2008年04期

7 鄧振淼;劉渝;;正弦波頻率估計(jì)的牛頓迭代方法初始值研究[J];電子學(xué)報(bào);2007年01期

8 齊國清;;幾種基于FFT的頻率估計(jì)方法精度分析[J];振動(dòng)工程學(xué)報(bào);2006年01期

9 王諾,戴逸民;用于衛(wèi)星通信的一類UQPSK載波恢復(fù)算法及其性能的研究[J];電子學(xué)報(bào);2004年07期

10 齊國清,賈欣樂;插值FFT估計(jì)正弦信號頻率的精度分析[J];電子學(xué)報(bào);2004年04期

相關(guān)碩士學(xué)位論文 前1條

1 劉銀恩;高精度頻率估計(jì)算法研究[D];南京理工大學(xué);2007年

，

本文編號：2503647