Wavelet Packet Transform For Signal Detection Under Non-gaussian Noise

Signal dection is one of the most important research branches in the signal process. The former detection methods are mostly based on the Gaussian noise, and soldom based on non-gaussian noise. However, in radar and communication fields, the supposed gaussian noise can not meet the requirements. Taking radar system as an example, the total noises in the communication channels with various random pulse-noise interference, do not meet gaussian distribution and it trails long. Therefore, the performance of the detection system based on gaussian noise is falling down rapidly. Wavelet transform analyses the signals or functions by the fine division which is coming from the retractility and movable characters of wavelet. It has the perfect performance of fine partly division and multiresolution, as it is fit for the signal process and becomes a new signal process technology. In the dissertation, it puts wavelet-packet decomposition into the study on non-gaussian noise. It offers a new signal dection method under non-gaussian noise backgroud. In the first chapter, it introduces the history of signal detection and the main work of the paper. In the second chapter, it introduces the basic theroy of signal detection, including the duality supposed detection and multiple supposed detection, the design principle for statistic signal detection system. It also gives the theory for the best receiver design according to the different adjudging rules on the statistic character of the signal and noise. In the third chapter, it introduces the basic theroy of the wavelet and the fundamental idea of the orhonormal wavelet-packet, which is coming from the multiresolution and the construction of orhonormal wavelet. The orhonormal wavelet-packet has many perfect characters...