Shang Hai-yan, Shui Peng-lang, Zhang Shou-hong, Zhang Ya-bin, Zhu Tian-qiao. Energy Integration Detection via Time-Frequency Distribution and Morphological Filtering[J]. Journal of Electronics & Information Technology, 2007, 29(6): 1416-1420. doi: 10.3724/SP.J.1146.2005.01381
Citation:
Shang Hai-yan, Shui Peng-lang, Zhang Shou-hong, Zhang Ya-bin, Zhu Tian-qiao. Energy Integration Detection via Time-Frequency Distribution and Morphological Filtering[J]. Journal of Electronics & Information Technology, 2007, 29(6): 1416-1420. doi: 10.3724/SP.J.1146.2005.01381
Shang Hai-yan, Shui Peng-lang, Zhang Shou-hong, Zhang Ya-bin, Zhu Tian-qiao. Energy Integration Detection via Time-Frequency Distribution and Morphological Filtering[J]. Journal of Electronics & Information Technology, 2007, 29(6): 1416-1420. doi: 10.3724/SP.J.1146.2005.01381
Citation:
Shang Hai-yan, Shui Peng-lang, Zhang Shou-hong, Zhang Ya-bin, Zhu Tian-qiao. Energy Integration Detection via Time-Frequency Distribution and Morphological Filtering[J]. Journal of Electronics & Information Technology, 2007, 29(6): 1416-1420. doi: 10.3724/SP.J.1146.2005.01381
Long duration integration of the interesting signal energy is a key to develop an effective detector under severe noise background in many applications. With the time-frequency concentration characteristic of the interesting signal, a new energy integration detect method is proposed in this paper based on the morphological filtering in the time-frequency plane. Firstly, the optimal kernel of the Cohens Time-Frequency Distribution (TFD) is designed and the TFD of the observation is calculated. Thereafter, the support region of strong energy is estimated by thresholding the TFD and morphological filtering the obtained binary image. Finally, the energy on the estimated region is integrated to judge whether a signal is present or not. Simulation results show that the proposed method is effective in low ratios of signal to noise case.
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