Research On Noise Suppression Of Wideband Chirp Signal

Wideband chirp signal is widely used in the military, radar and sonar areas. However, due to the target echo characteristics of broadband radar with random parameter features, it is totally different from the conventional narrowband radar. Therefore, how to process noise suppression for the radar echo information becomes a hot topic in the field of signal processing. Although in the past few decades, the theory and algorithms related to signal noise suppression have been developed, most of the methods are no longer applicable for wideband chirp signal.In this paper, we expand the research of the method of signal noise suppression based on characteristics and processing methods for wideband chirp signals. Starting from improving the signal de-noising effect, reducing the complexity of the algorithm, we study the effects of different types of noise on the broadband chirp signal, as well as the suppressing effect of different de-noising algorithms for the broadband chirp signal. At the same time, a large number of simulation experiments demonstrate the effectiveness and superiority of the de-noising method of this article.The main content and innovation of this study are as follows:First, study and analyze different noises impacting on wideband chirp signal. Radar range resolution can use very short pulses to be significantly improved. However, using short pulses would reduce the average transmission power, which is directly related to the signal to noise ratio of the receiver, it is usually desirable to increase the pulse width while maintaining sufficient resolution. Pulse compression technology will make this expectation possible. Pulse compression radar has a strong anti-jamming capability, limiting the interference effect of ordinary noise. Thus, this paper firstly studies of different noise interference on wideband chirp signal. Simulation results show the effects of different kinds of noise interference vary.Secondly, study the signal de-noising methods based on wavelet transform, from the filtering de-noising method of wavelet decomposition and reconstruction based on the concept of multi-resolution analysis to the de-noising algorithm of wavelet transform modulus maxima based on Singularity Detection theory, and the de-noising method about nonlinear wavelet transform threshold. Then we elaborate the de-noising theory based on the sparse decomposition and analyze the greedy matching pursuit algorithm, and give a detailed algorithm steps. At the same time, this paper combines with wavelet de-noising method to further study sparse representation. For the wideband chirp signal noise suppressing, simulation results show that: in de-noising effect aspect, the methods based on wavelet transform is generally superior to the methods of sparse decomposition; in terms of computing speed, the former is obviously higher than the latter.Finally, study the signal de-noising method based on Empirical Mode Decomposition. We depth study the three de-noising algorithms based on the method. The original method about modal correlation does not consider the noise component in question may contain useful signal. We propose a new method about modal correlation based on wavelet de-noising algorithm. Simulation results show that the de-noising effect of new algorithm was significantly better than the original algorithm. Then we combine the method of wavelet transform and sparse representation, proposing another new algorithm based on Empirical Mode Decomposition. Simulation results demonstrating the effectiveness of the algorithm, Signal to Noise Ratio has been improved to some extent.