低载噪比高动态信号相位估计方法研究

发布时间：2018-05-05 04:33

本文选题：高动态 + 低载噪比　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：信号的参数估计问题在雷达信号处理、生物医学、测控技术、振动信号分析处理和声纳探测等众多领域中有着极其重要的理论和应用价值。通常情况下,在物理量的计量和测试过程中,物理系统会受到环境和人为因素的干扰,信号均会不同程度被噪声所污染。实际研究中常常要面对低信噪比下对信号的检测和参数估计,故发现一种高效的信号参数估计方法,在低信噪比等环境下对信号的频率、相位和幅值等参数进行估计后对信号恢复是非常有意义而且必要的。在深空测控通信中,通信距离遥远,电磁环境复杂,信号的损耗严重,使得接收信号的信噪比极低,且飞行器与接收机间高速相对移动使得载波产生高达(-300KHz,300KHz)多普勒频偏以及高达(-3KHz/s,3KHz/s)的一次频率变化率,有时甚至会产生很大的二次频率变化率,这对接收机进行有效的信号参数估计提出了很大的挑战。在工程实践中,如通信、仪表、电力、光学应用、故障诊断等领域,存在大量对信号的相位进行高效并且快速估计的需求。在通信系统中,如果采用了QAM或者QPSK等相位调制技术,只有在输出端对信号进行适当的处理,快速准确的估计出各个码元载波的初相位,才能把星座图正确的恢复出来,从而完成正常的解码过程。本文对强噪声高动态背景下信号的瞬时相位估计方法进行了研究,主要工作如下:1.分析了信号瞬时相位估计的一般思路,即将瞬时相位分为相位偏移和初始相位两部分分别进行估计的方法。2.提出了一种新的频率估计方法,即时域匹配周期图捕获算法和多次拟合相结合的频率估计方法。该方法可以在较低载噪比和中心频率高动态变化的环境下对中心频率和多普勒变化率进行较高精度的估计。此外,还提出了基于三次样条插值与数值积分相结合的离散数据积分方法,使得估计出来的频率值可以转化为相位偏移值。3.对传统的相位估计方法进行了仿真,比较了其在高动态和低载噪比环境下的表现,发现在高动态环境下大部分传统的信号相位估计方法都会失效。所以针对这种情况提出了利用频率和多普勒变化率的估计值产生参考信号对信号中心频率的变化率进行削弱的方法。此外还提出了正弦信号放大算法。该算法可以对强噪声环境下正弦信号的相关性进行增强,降低噪声对信号的影响,提高信噪比。最后将这两种方法与互相关法结合,提出了完整的算法。该方法在低载噪比和高动态环境下表现出了对传统方法优越的性能。
[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.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.23

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