基于时频分析的人体红外热信号检测算法
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广东工业大学华立学院,广州511325

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TN911

基金项目:

2012广东省质量工程人才培养实验区(粤教高函[2012]204号)项目、2015年广东省大学生科技创新培育(pdjh2015b0942)项目、2012广东省质量工程项目“机电综合技能实训中心”(粤教高函[2012]204号)


Infrared thermal signal detection algorithm based on time frequency analysis
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Huali College,Guangdong University of Technology, Guangzhou 511325, China

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    摘要:

    救援机器人通过对人体红外热信号进行有效检测,实现对遇险人员的远程识别与救援,传统的人体红外热信号检测采用声谱图检测方法,在信噪比较低的环境下检测效果不好。提出一种基于时频分析的人体红外热信号检测算法,构建强干扰下的人体红外释热信号参量模型,采用多普勒频率模糊数搜索的方法完成多方向相位的人体红外释热信号动态平滑处理,对非平稳时变信号进行时频分析,剔除负频部分,实现抗干扰滤波,通过后置的高阶累积量切片算子进行Hough变换处理,使得信号在时频面的聚焦累积量增大,而噪声被抑制,实现信号检测。仿真结果表明,采用该算法进行人体红外热信号检测的准确检测概率较高,抗干扰能力较强,提高了救援机器人的搜索识别能力。

    Abstract:

    The rescue robot can detect the human bodys infrared thermal signal effectively, and realize the remote recognition and rescue of distress personnel. The traditional method used spectrogram detection method, but the detection effect was not good in low SNR environment. A new method of infrared thermal signal detection is proposed based on time frequency analysis. A parametric model of the human body infrared heat release signal is constructed, and the dynamic smoothing process of the human body infrared heat release signal is processed by the Doppler frequency fuzzy number search method. The timefrequency analysis of nonstationary time varying signal is carried out, and the negative frequency part is eliminated. Antiinterference filter is realized. The Hough transform is implemented by the postpositive high order accumulated amount of the signal, the focus of signal in the time frequency plane is increased. The signal is suppressed and the noise is suppressed. The simulation results show that this algorithm has higher accuracy and better antiinterference ability, and the search and recognition ability of the rescue robot is improved.

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陆兴华,陈锐俊,池坤丹.基于时频分析的人体红外热信号检测算法[J].国外电子测量技术,2016,35(2):55-58

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  • 在线发布日期: 2016-03-29
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