發(fā)布時間：2018-05-05 04:33

  本文選題：高動態(tài) + 低載噪比　； 參考：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：信號的參數(shù)估計(jì)問題在雷達(dá)信號處理、生物醫(yī)學(xué)、測控技術(shù)、振動信號分析處理和聲納探測等眾多領(lǐng)域中有著極其重要的理論和應(yīng)用價值。通常情況下,在物理量的計(jì)量和測試過程中,物理系統(tǒng)會受到環(huán)境和人為因素的干擾,信號均會不同程度被噪聲所污染。實(shí)際研究中常常要面對低信噪比下對信號的檢測和參數(shù)估計(jì),故發(fā)現(xiàn)一種高效的信號參數(shù)估計(jì)方法,在低信噪比等環(huán)境下對信號的頻率、相位和幅值等參數(shù)進(jìn)行估計(jì)后對信號恢復(fù)是非常有意義而且必要的。在深空測控通信中,通信距離遙遠(yuǎn),電磁環(huán)境復(fù)雜,信號的損耗嚴(yán)重,使得接收信號的信噪比極低,且飛行器與接收機(jī)間高速相對移動使得載波產(chǎn)生高達(dá)(-300KHz,300KHz)多普勒頻偏以及高達(dá)(-3KHz/s,3KHz/s)的一次頻率變化率,有時甚至?xí)�產(chǎn)生很大的二次頻率變化率,這對接收機(jī)進(jìn)行有效的信號參數(shù)估計(jì)提出了很大的挑戰(zhàn)。在工程實(shí)踐中,如通信、儀表、電力、光學(xué)應(yīng)用、故障診斷等領(lǐng)域,存在大量對信號的相位進(jìn)行高效并且快速估計(jì)的需求。在通信系統(tǒng)中,如果采用了QAM或者QPSK等相位調(diào)制技術(shù),只有在輸出端對信號進(jìn)行適當(dāng)?shù)奶幚?快速準(zhǔn)確的估計(jì)出各個碼元載波的初相位,才能把星座圖正確的恢復(fù)出來,從而完成正常的解碼過程。本文對強(qiáng)噪聲高動態(tài)背景下信號的瞬時相位估計(jì)方法進(jìn)行了研究,主要工作如下:1.分析了信號瞬時相位估計(jì)的一般思路,即將瞬時相位分為相位偏移和初始相位兩部分分別進(jìn)行估計(jì)的方法。2.提出了一種新的頻率估計(jì)方法,即時域匹配周期圖捕獲算法和多次擬合相結(jié)合的頻率估計(jì)方法。該方法可以在較低載噪比和中心頻率高動態(tài)變化的環(huán)境下對中心頻率和多普勒變化率進(jìn)行較高精度的估計(jì)。此外,還提出了基于三次樣條插值與數(shù)值積分相結(jié)合的離散數(shù)據(jù)積分方法,使得估計(jì)出來的頻率值可以轉(zhuǎn)化為相位偏移值。3.對傳統(tǒng)的相位估計(jì)方法進(jìn)行了仿真,比較了其在高動態(tài)和低載噪比環(huán)境下的表現(xiàn),發(fā)現(xiàn)在高動態(tài)環(huán)境下大部分傳統(tǒng)的信號相位估計(jì)方法都會失效。所以針對這種情況提出了利用頻率和多普勒變化率的估計(jì)值產(chǎn)生參考信號對信號中心頻率的變化率進(jìn)行削弱的方法。此外還提出了正弦信號放大算法。該算法可以對強(qiáng)噪聲環(huán)境下正弦信號的相關(guān)性進(jìn)行增強(qiáng),降低噪聲對信號的影響,提高信噪比。最后將這兩種方法與互相關(guān)法結(jié)合,提出了完整的算法。該方法在低載噪比和高動態(tài)環(huán)境下表現(xiàn)出了對傳統(tǒng)方法優(yōu)越的性能。
[Abstract]:The problem of signal parameter estimation is of great theoretical and practical value in many fields such as radar signal processing biomedical measurement and control technology vibration signal analysis and sonar detection and so on. In general, in the process of measurement and measurement of physical quantities, the physical system will be disturbed by environmental and human factors, and the signals will be polluted by noise in varying degrees. In the practical research, we often face the detection and parameter estimation of the signal under the low SNR, so we find an efficient signal parameter estimation method, which can estimate the frequency of the signal in the low signal-to-noise ratio (SNR) environment. It is very important and necessary to estimate the parameters such as phase and amplitude for signal recovery. In the deep space TT & C communication, the communication distance is long, the electromagnetic environment is complex and the signal loss is serious, which makes the signal-to-noise ratio of the received signal extremely low. And the relative high-speed movement between the aircraft and the receiver causes the carrier to produce up to -300KHz) Doppler frequency offset and a frequency change rate of up to -3KHz / skHz / s, and sometimes even a very large secondary frequency change rate. This poses a great challenge to the effective signal parameter estimation of the receiver. In engineering practice, such as communication, instrumentation, power, optical applications, fault diagnosis and other fields, there is a large number of efficient and fast signal phase estimation requirements. In the communication system, if the phase modulation technology such as QAM or QPSK is adopted, only when the signal is properly processed at the output end, the initial phase of each symbol carrier can be estimated quickly and accurately, and the constellation diagram can be restored correctly. In order to complete the normal decoding process. In this paper, the instantaneous phase estimation method for strong noise and high dynamic background is studied. The main work is as follows: 1. In this paper, the general idea of instantaneous phase estimation is analyzed, that is, the instantaneous phase is divided into two parts: phase offset and initial phase. In this paper, a new frequency estimation method is proposed, which combines the instantaneous domain matching periodic graph capture algorithm with multiple fitting. This method can estimate the center frequency and Doppler change rate with high dynamic change in low carrier noise ratio and center frequency. In addition, a discrete data integration method based on cubic spline interpolation and numerical integration is proposed, which can transform the estimated frequency value into phase offset value. The traditional phase estimation method is simulated, and its performance in high dynamic and low load noise ratio environment is compared. It is found that most of the traditional signal phase estimation methods will fail in high dynamic environment. Therefore, a method is proposed to weaken the rate of change of signal center frequency by using the estimation of frequency and Doppler rate to generate reference signal. In addition, a sinusoidal signal amplification algorithm is proposed. This algorithm can enhance the correlation of sinusoidal signal in strong noise environment, reduce the influence of noise on signal, and improve the signal-to-noise ratio (SNR). Finally, a complete algorithm is proposed by combining the two methods with the cross-correlation method. The performance of this method is superior to the traditional method under low load to noise ratio and high dynamic environment.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN911.23

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