【摘要】：在通信領(lǐng)域與信號處理中,微弱正弦信號的參數(shù)估計是一個基礎(chǔ)性的并且被大量研究的問題。當前,微弱正弦信號的參數(shù)估計已經(jīng)被廣泛的應(yīng)用于信號恢復(fù)、語音信號處理、雷達目標定位等諸多領(lǐng)域。因此,對于微弱正弦信號的參數(shù)估計問題的研究具有重要的理論意義與實際應(yīng)用價值。本文對DFT算法、最小二乘算法進行了分析,對于微弱正弦信號,這些算法的估計值與真實值相差較大。針對此問題,本文對DFT算法和最小二乘法進行改進,分別得到了基于DFT和DWT的頻率估計算法,基于DWT的相位估計算法及改進的幅值算法。本文的主要工作如下:1.給出了DFT頻率估計的改進算法。該算法提高了頻率估計的精度,公式推導(dǎo)比較簡單,同時改進算法的計算量低于DFT算法的計算量,易于工程實現(xiàn);2.給出了基于離散小波變換的頻率估計算法以及頻率校正的迭代算法。使用小波變換對信號進行處理,從而獲得兩段新的序列,對獲得的兩段不同長度的序列分別實施離散傅里葉變換,通過推導(dǎo)得到頻率的粗估計值,在此基礎(chǔ)上,給出了頻率校正的迭代算法,并對性能進行了分析;3.給出了基于DWT的相位估計算法。利用小波變換對信號處理,得到長度不同的序列,并對得到的序列實施Z變換,結(jié)合序列的構(gòu)造方式通過推導(dǎo)得到相位的估計值。將該算法與以往算法進行仿真實驗對比,可以看出在低信噪比下,該算法有較好的估計精度;4.給出了正弦信號幅值估計算法。并將此算法與基于自相關(guān)函數(shù)的幅值估計進行仿真實驗對比了,可以看出該算法具有較高的估計精度。
[Abstract]:In the field of communication and signal processing, the parameter estimation of weak sinusoidal signal is a basic and widely studied problem. At present, the parameter estimation of weak sinusoidal signal has been widely used in many fields, such as signal recovery, speech signal processing, radar target location and so on. Therefore, the research on parameter estimation of weak sinusoidal signal has important theoretical significance and practical application value. In this paper, the DFT algorithm and the least square algorithm are analyzed. For the weak sinusoidal signal, the estimated value of these algorithms is quite different from the real value. In order to solve this problem, the DFT algorithm and the least square method are improved in this paper. The frequency estimation algorithms based on DFT and DWT, the phase estimation algorithm based on DWT and the improved amplitude algorithm are obtained, respectively. The main work of this paper is as follows: 1. An improved algorithm for DFT frequency estimation is presented. The algorithm improves the accuracy of frequency estimation, and the formula derivation is relatively simple, and the computational complexity of the improved algorithm is lower than that of DFT algorithm, which is easy to be realized in engineering. 2. A frequency estimation algorithm based on discrete wavelet transform and an iterative algorithm for frequency correction are presented. The wavelet transform is used to process the signal, and two new sequences are obtained. The discrete Fourier transform is applied to the two sequences of different lengths, and the coarse estimation of the frequency is derived. The iterative algorithm of frequency correction is given, and the performance is analyzed. 3. A phase estimation algorithm based on DWT is presented. The wavelet transform is used to process the signal and the sequence of different length is obtained. The Z transform is applied to the sequence and the phase estimation is obtained by deducing the method of constructing the sequence. By comparing the algorithm with the previous algorithms, we can see that the algorithm has better estimation accuracy under low SNR. 4. An algorithm for estimating the amplitude of sinusoidal signals is presented. By comparing this algorithm with the amplitude estimation based on autocorrelation function, it can be seen that the algorithm has high estimation accuracy.
【學位授予單位】：哈爾濱工程大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN911.23

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本文編號：2307791