本文選題：參數(shù)估計 + Alpha穩(wěn)定分布　； 參考：《西安電子科技大學》2014年碩士論文

【摘要】：近年來,隨著通信環(huán)境的日趨復雜,基于高斯白噪聲環(huán)境的數(shù)字信號處理方法在實際通信環(huán)境下存在很多弊端。實際通信系統(tǒng)中的噪聲往往具有顯著的尖峰脈沖特性,且通常以Alpha穩(wěn)定分布模型進行建模。PSK信號憑借其較強的抗干擾能力,廣泛應(yīng)用于高、中速數(shù)據(jù)傳輸。研究非高斯Alpha穩(wěn)定分布噪聲下PSK信號的參數(shù)估計可以為信號的解調(diào)、識別、恢復等后續(xù)工作提供依據(jù),是非合作通信信號處理過程中必不可少的環(huán)節(jié)。因此,本文對Alpha穩(wěn)定分布噪聲下的PSK信號的部分參數(shù)進行估計,所取得的主要研究成果如下:1.針對Alpha穩(wěn)定分布噪聲下PSK信號的載頻估計方法在低信噪比條件下性能較差的問題,提出了一種基于循環(huán)共變譜的PSK信號載頻估計新方法。該方法通過構(gòu)建信號的循環(huán)共變函數(shù),推導出了其循環(huán)共變譜,并通過譜截面特征的提取以及該特征與載頻之間的特定關(guān)系,實現(xiàn)非高斯Alpha穩(wěn)定分布噪聲下PSK信號的載頻估計。此外,本文還從理論上分析了Alpha穩(wěn)定分布噪聲下的PSK信號載波頻率估計的克拉美羅界(CRLB)。仿真結(jié)果表明,在Alpha穩(wěn)定分布噪聲下,該方法的估計性能在低信噪比下較好。2.針對Alpha穩(wěn)定分布噪聲下PSK信號的碼元速率估計困難的問題,提出了一種基于分數(shù)低階離散域累加平均的PSK信號碼元速率估計新方法。該方法首先對離散時域點及其累加值進行分數(shù)低階運算,然后構(gòu)建分數(shù)階離散域累加平均時域圖,則相位跳變的位置點會出現(xiàn)峰值特性,再通過搜索并計算任意相鄰峰值譜線的時間距離,確定最小時間距離,從而得出PSK信號的碼元速率。此外,本文還從理論上分析了Alpha穩(wěn)定分布噪聲下PSK信號的碼元速率估計的克拉美羅界。仿真結(jié)果表明,在Alpha穩(wěn)定分布噪聲下,該方法的估計性能較好且計算復雜度較低。
[Abstract]:In recent years, with the increasing complexity of communication environment, the digital signal processing method based on Gao Si white noise environment has many drawbacks in the actual communication environment. The noise in practical communication system often has the characteristic of sharp spike pulse, and the model of Alpha stable distribution model is usually used to model .PSK signal, because of its strong anti-jamming ability, it is widely used in high and medium speed data transmission. The parameter estimation of PSK signal under non-Gao Si Alpha stable distributed noise can provide basis for signal demodulation, identification, recovery and so on. It is an essential link in the process of non-cooperative communication signal processing. Therefore, this paper estimates some parameters of PSK signal under Alpha stable distributed noise, and the main research results are as follows: 1. A novel carrier frequency estimation method for PSK signals based on cyclic covariant spectrum is proposed to solve the problem that the carrier frequency estimation method of PSK signals with stable distribution of Alpha noise is of poor performance under low SNR. By constructing the cyclic covariant function of the signal, the cyclic covariant spectrum of the signal is derived, and the carrier frequency estimation of the PSK signal under the non-Gao Si Alpha stable distribution noise is realized by extracting the spectral cross-section feature and the specific relationship between the characteristic and the carrier frequency. In addition, in this paper, the Clemero bound for the carrier frequency estimation of PSK signals under the stable distributed noise of Alpha is analyzed theoretically. The simulation results show that the estimation performance of this method is good at low SNR under the condition of Alpha stable distribution noise. Aiming at the difficulty of estimating the symbol rate of PSK signals under the stable distributed noise of Alpha, a new method for estimating the rate of PSK number elements based on the accumulative average of fractional low order discrete domain is proposed. In this method, the discrete time domain points and their accumulative values are first performed fractional low order operations, and then the fractional discrete domain accumulative mean time domain maps are constructed, and the peak value of the position points of the phase jump will appear. Then the minimum time distance is determined by searching and calculating the time distance of any adjacent peak line, and the symbol rate of PSK signal is obtained. In addition, this paper theoretically analyzes the Clemero bound for the estimation of the symbol rate of PSK signals under the stable distribution of Alpha noise. The simulation results show that the proposed method has better estimation performance and lower computational complexity under the stable distribution of Alpha noise.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN911.23

【參考文獻】

相關(guān)期刊論文 前1條

1 姚帥;方世良;王曉燕;;有色噪聲背景下的水聲跳頻信號參數(shù)估計[J];東南大學學報(自然科學版);2014年01期

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本文編號：1939726