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中文摘要：
针对通信监测实际环境中现有方法难以有效提取时频分量的问题，提出一种基于改进TFD-Hough变换的时频分量检测算法。在信号分量数目未知的条件下，该方法能充分利用时频分布面各分量的幅值具有线性聚集的特点，通过覆盖聚类和感知编组实现信号分量的逐次提取和参数估计，避免了全局检测中因分量能量差异导致的误检且无法获取目标位置信息的缺陷。实验结果验证了所提方法的有效性，可满足于异常通信信号的主动识别。
英文摘要：
To solve the problem that the existing methods cannot effectively extract time-frequency component in the real com- munication monitoring environment, a novel method for the time-frequency component detection is proposed on the basis of the improved TFD-Hough transformation. Under the circumstance that the number of detected component is unknown, the proposed method can take full advantage of the linearity clustering trait of the magnitude of component in time-frequency distribution, and combine the covering clustering algorithm with perceptual organization to implement the procedure of extracting and detecting parameters of signal component one by one, avoiding the flaws brought by the energy difference and the lack of the location information of the target in global detection. The experimental results demonstrate the validity of the proposed method, which can meet the requirement of actively identifying the abnormity of communication signal.
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