Applications of the Optimal Gaussian Kernel Time-Frequency Analysis for Acoustic Signal Detection

• Main Authors: Chen, Jiang-Ann, 陳建安
• Other Authors: Fu-Shieng Lu
• Format: Others
• Language: zh-TW
• Published: 1997
• Online Access: http://ndltd.ncl.edu.tw/handle/45271969757705011840

碩士 === 國立海洋大學 === 電機工程學系 === 85 === In diverse fields of application, such as telecommunicatios, telemetry, sonar, and radar,the received signals are generally nonstationary, and they must be processed by appropriate time-frequency analysis methods for obtaining genuine information. For multicomponent nonstationary signals, each time-frequency distribution corresponds to a kernel that controls the cross-terms suppression properties. Selection of a fixed kernel limits the class of signals for which the distribution performs well.For analysis of a broad class signals, a signal- dependent kernel is recommended. In this thesis, a new procedure, based on optimal criteria and Gaussian kernel, is introduced for signal-dependent kernel design.We use Matlab and LabVIEW to build up the processing for conducting simulation and experiments with various nonstationary chirpsignals. The simulation and experimental results show the algorithm is efficient.