A Study Of Phase Estimation Methods Of High Dynamic Signal Under Strong Noise

Parameter estimation problems of signal has important theoretical and practical value in many fields, such as radar signal processing, biomedical, measurement and control technology, vibration signal analysis and processing, sonar and so on. Under normal circumstances, during the process of the measurement and testing process, physical systems are often subject to environmental and human interference, so the signal will be subject to different levels of noise. Therefore, we often need to do the signal detection and parameter estimation at a low signal to noise ratio. It is meaningful for us to find a high efficiency method to estimate the parameters of a signal under the low SNR and high dynamic environment.In monitoring and control communication, We often face a situation with long communication distance, complex electromagnetic environment, a serious loss of signal and the relative speed between the aircraft and the receiver carrier generation mobile makes up(-300 KHz, 300KHz) Doppler offset and up(-3KHz / s, 3KHz / s) of a frequency change rate, and sometimes even have a great secondary frequency rate of change, which presented a great challenge to effective parameter estimation of receiver signal.In communications, instrumentation, electrical, optical applications, fault diagnosis and other engineering fields, there are a lot of the signal phase high-precision, high efficiency, rapid estimation problem. For example, in using QAM, PSK modulation communication system, only the receiving end of each symbol period for fast initial phase of the carrier estimate constellation properly restored, to achieve the correct decodingIn this paper, under the environment of strong noise and high dynamic, the methods of the estimation of instantaneous phase of a signal were studied, the main work is as follows:1. In this paper, we analyze the general idea to estimate the instantaneous phase of a signal, which is we proposed a method to divide the instantaneous phase into two parts to estimate.2. I have proposed a frequency estimation method which is a combination of a capture algorithm based on time-domain matching cycle diagram and fitting for many times, making it possible to do a high precision estimation under a lower SNR and high dynamic environment. Furthermore, discrete data integration method is proposed that is based on a combination of cubic spline interpolation and numerical integration, making the estimated frequency value can be converted to a phase offset.3. I simulated conventional phase estimation methods and compared its performance under lower SNR and high dynamic environment. Then, I found most of the traditional estimation method will be disabled under high dynamic under high dynamic and low SNR environment. So for this situation, I propose a method, which is using the estimated value of frequency and modulation frequency to generate a reference signal which is used to weaken the change rate of the center frequency of the signal. In addition, I also proposed a sinusoidal signal amplification algorithms. The algorithm can be used to enhance the correlation of a sinusoidal signal which is under a strong noise environment and reduce the effect of noise.Finally, these two methods were combined with the correlation method, and a complete algorithm was presented which shows better performance compared to traditional methods.