| Citation: | GUO Xiaotao, WANG Xing, ZHOU Dongqing, et al. Transient communication signal detection under non-Gaussian noise based on improved HHT[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(8): 1684-1692. doi: 10.13700/j.bh.1001-5965.2016.0576(in Chinese)
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Based on the characteristics of transient communication signals and non-Gaussian noise, the corresponding signal models were established, and a novel algorithm of transient communication signal detection under non-Gaussian noise was proposed based on the improved Hilbert-Huang transform (HHT), which takes the advantage of HHT in processing non-linear and non-stationary signals. The improved detection algorithm was divided into two sections:ensemble empirical mode decomposition (EEMD) and filter of intrinsic mode function (IMF) components. First, signals were decomposed into several IMF components by adding random white noise and averaging, and then false components were eliminated by energy variance and correlation, through which transient signals aliased in the non-Gaussian noise can be detected effectively. Simulation compares the detection efficiency of HHT and the proposed algorithm, and the results demonstrate that the proposed algorithm can reduce the influence of model mixing and false frequency caused by HHT and achieve more accurate analysis to the time-frequency characteristics of transient communication signal.
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