Study On Time-delay And Doppler Estimation Of Chirp Signal Based On Wavelant

Chirp signal (linear modulated signal, LFM) is a very important signal indigital signal processing community. It is widely used in many systems, e.g., communication, radar, sonar, seismography, geology and ioengineering. The research on Chirp signal is of significance in both signal processing theory and its practice applications. However, the correlation function of Chirp signal contains time variable t, i.e. the Chirp signal is nonstationary. So it brings difficulty in our study.The work of this paper includes two primary questions: time delay estimation and Doppler stretch delay estimation of Chirp signals. Various techniques have been used to perform Chirp signals time delay estimations, but they almost have disadvantages of high complexity and huge computational cost. The other shortcoming is that the additive noise of these methods must be restricted in Gaussian noise. Moreover, the mature approaches are mostly based on assume of stationary model. The excellent methods of Chirp signal time delay estimation are even less. To solve these questions, here we propose a set of new Chirp signal processing methods based on quadratic form transformation. The main tasks are generalized as:1. Study on the wavelants.Most of existing Chirp frequency parameter estimation methods are based on white Gaussian noise assumption. This assumption is in favor of theory analysis and processing, but noise is often more complicated in practice. So these approaches are no longer suitable. In this paper, Wavelant is combined by the wavelet transform and higher-order cumulants, and at the same time have the nature of wavelet transform and higher-order cumulants. Therefore, in Gaussian noise environment, joint time delay and doppler stretch estimation can be gained by the nature of this algorithm. 2. Joint time delay and doppler stretch estimation of the single-component Chirp signal based on wavelant.The Chirp signal is non-stationary signal, according to the average time and sets average of the single-component Chirp signal, gaining the form of wavelant in single Chirp signals. This algorithm estimates joint time delay and doppler stretch coefficient in Gaussian noise environment. Simulation results show that this new estimation algorithms can suppress Gaussian colored noise and their computational loads are smaller than most nonstationary joint estimation approaches.3. Joint time delay and doppler stretch estimation of Chirp signal based on wavelant.Multi-component Chirp signal applies in radar, communications and other communications applications broader, so this article study joint time delay and doppler stretch coefficient using the multi-component Chirp signal. At the same time, the application of wavelant have the nature to suppress Gaussian noise, the algorithm can accurately estimate the time delay and Doppler expansion coefficient. Simulation results show that this new estimation algorithms can suppress Gaussian noise. Compared with general approaches, the methods in this paper have many prominent virtues:1. They have good noise-restrain ability. Because of the introduction of the modern cross-spectral estimation methods, the approaches in this paper can work in low SNR almost without any prior information about colored noise.2. They can get accurate estimation results even with short data sequences. It makes these methods more applicable to engineering practice.3. They all have high resolution and stability.Generalized speaking, we consider that both the Chirp time delay estimation methods and the Chirp signal doppler stretch estimation methods proposed in this paper have academic significance and engineering applicable value. They are effective and can put into practice.