Weak radar signal de-noising by using genetic algorithm

Radar is one of the major application areas of communication systems. Radar signals can be corrupted with the noise due to environmental or human-induced causes. Thus, determination of the actual signal might be very hard.In this thesis, weak radar signal denoising is aimed. Therefore, Wavelet Transform and Wavelet Packet Transform is used. When performing Wavelet Transformations, choosing the wavelet family type, the entropy type and the decomposition level is important. Moreover, choosing the threshold function for thresholding procedure is important too.In this study, Genetic Algorithm is proposed as the intelligent. Because of this optimization structure, the best wavelet family type, entropy type and decomposition level is determined. Moreover, the Fuzzy s-function is used as thresholding function. The parameters of the Fuzzy s-function are chosen for the best performance criterion.The proposed weak signal denoising structure is compared with the other algorithms that have already been proposed in literature. The performance comparison is carried out with both statistical Root Mean Square Error and Correlation Coefficient.The results show the superiority of our proposal comparable with the other methods.Key-words: Weak Radar Signal, Denoising, Genetic Algorithms, Wavelet Transform, Thresholding, Root Mean Square Error, Correlation Coefficient.