MA Wen-gang, WANG Xiao-peng, TIAN Jun-wei
(School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)
Abstract： The radar echo signal of non-stationary and singular points usually contains false echoes, which affects the recognition and measurement of liquid level echo signal. In order to eliminate false echo interference and improve the recognition and measurement accuracy of the liquid level gauge, a method of echo recognition and correction based on adaptive least mean square (LMS) is proposed. The short-time amplitude function and short-time zero crossing rate function are combined to recognize the echo signal. The weight vector iteration and updating weight coefficients are obtained by LMS method. The echo signal is recognized and the false echo interference is suppressed. The experimental results show that the level echo signal can be accurately recognized by this method, and level measurement accuracy can reach 0.47% F.S. Compared with other denoising methods, adaptive LMS can keep the signal singularity characteristics while suppressing the noise. Moreover, it has better robustness.
Key words： guided wave radar; liquid level gauge; least mean square (LMS); echo correction
CLD number： TP273 Document code： A
Article ID： 1674-8042（2017）04-0328-06 doi： 10.3969/j.issn.1674-8042-2017-04-004
References
［1］ZHANG Ning, HUANG Yang. Study on the measurement of the level meter. Journal of Metrology, 2008, 29 (S1): 104-106.
［2］MA Ping, HE Chang-wei, LIU Sen, et al. Study on a novel triangular swept frequency microwave interferometer and its signal processing method. Journal of Microwave Science, 2007, 23 (4): 58-62.
［3］LIU Chang, ZHANG Guo-guang. The design of intelligent temperature transmitter based on HART protocol. In: Instrumentation, Measurement, Computer, Communication and Control (IMCCC), Second International Conference on IEEE, 2012: 1499-1502.
［4］Pereira M D, Postolache O, Girao P. HART protocol analyzer based in LabVIEW. In: Proceedings of IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003: 174-176.
［5］TU Gang-yi, JIN Shi-jun, ZHU Xue-fen, et al. Compensation of GPS non-Gaussian pseudorange error based on improved particle filter algorithm. Journal of Electronic Measurement and Instrument, 2009, 23(6): 24-28.
［6］Arthur E, Pece C. Contour tracking based on marginalized likelihood ratios. Image and Vision Computing, 2006, 24(3): 301-317.
［7］Torrea D, Ghinamo G, Detoma E, et al. Analysis of the accuracy of indoor GNSS measurements and positioning solution. In: Proceedings of European Navigation Conference-Global Navigat-ion Satellite Systems, ENC-GNSS, 2008: 22-25.
［8］YANG Jian, YAO Zhi-cheng. A simple digital filtering method. Chinese Journal of Scientific Instrument, 2009, 25 (1): 733-734.
［9］YANG Xu-fei, ZHANG Wei, YANG Yu-yao. Denoising technology of radar life signal based on lifting wavelet transform. Acta Optica Sinica, 2014, 34(3): 58-59.
［10］WU Gang, WANG Chang-men, BAO Jing-dong, et al. Wavelet thresholding denoising method based on adaptive threshold function. Journal of Electronics and Information Technology, 2014, 36(6): 78-79.
［11］MA Peng, HE Chen-wang, LIU Shu-zhang, et al. Study on a novel triangular swept frequency microwave interferometer and its signal processing method. Journal of Microwave Science, 2007, 23(4): 58-62.
［12］SHI Wang, CHEN Ke, GUO Hai-bin, et al. Wavelet-basedde-noising of positron emission tomography scans. Journal of Scientific Computing, 2012, 50(3): 665-677.
基于自适应LMS的导波雷达液位计回波识别与校正
麻文刚，王小鹏，田俊伟
（兰州交通大学 电子与信息工程学院,甘肃 兰州730070）
摘要:非平稳及多奇异点的雷达回波信号包含虚假回波，影响液位回波信号的识别与液位测量。为解决雷达液位计的虚假回波干扰问题，提高液位识别与测量精度，提出一种回波识别与校正方法。将短时幅度函数与短时过零率函数结合，利用函数逐帧地对回波信号计算，识别液位回波信号；通过自适应最小均方误差进行系统的权矢量迭代，更新权系数，对回波信号进行处理，进行抑制虚假回波干扰。实验结果表明:该方法能够准确识别液位回波信号；液位测量精度可达到0-42%F-S，相比于其他去噪方法，该方法在抑制噪声的同时能较好地保留信号奇异性特征，有较好的鲁棒性。
关键词:导波雷达； 液位计； LMS； 回波校正
引用格式：MA Wen-gang, WANG Xiao-peng, TIAN Jun-wei. Echo recognition and correction for guided wave radar level based on adaptive LMS . Journal of Measurement Science and Instrumentation, 2017, 8(4)： 328-333. ［doi： 10.3969／j.issn.1674-8042.2017-04-004］
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