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基于RBFNN的地电流场强区域指纹库构建方法
作者:
作者单位:

1.北京信息科技大学高动态导航技术北京市重点实验室 北京 100192;2.北京信息科技大学现代测控技术教育部 重点实验室 北京 100192

中图分类号:

TN92; TN929.4

基金项目:

国家自然科学基金(61971048)、北京市自然科学基金(4244091)项目资助


Construction method of regional fingerprint database of ground current field strength based on RBFNN
Author:
  • Zhang Zhicheng

    Zhang Zhicheng

    1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China；2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China
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  • Su Zhong

    Su Zhong

    1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China；2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China
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  • Zhao Hui

    Zhao Hui

    1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China；2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China
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  • Li Fei

    Li Fei

    1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China；2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China
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  • Sun Zhenzhen

    Sun Zhenzhen

    1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China；2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China
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Affiliation:

1.Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Information Science and Technology University， Beijing 100192,China;2.Key Laboratory of Modern Measurement and Control Technology,Ministry of Education, Beijing Information Science and Technology University，Beijing 100192,China

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    摘要:

    基于场强为特征的地电流场广泛应用于物探、地震监测、透地通信等领域，由于区域地电流场强存在变异，难以建立地电流场强区域指纹库。本研究提出一种基于RBFNN的地电流场强区域指纹库构建方法。通过分时十字注入构建区域地电流场，在不同检测点通过正交电极检测地电流场信号提取地电流场强指纹特征。采用RBFNN拟合Kriging插值中的场强变异函数模型，通过Kriging插值估计细粒度地电流场强区域指纹特征，根据估计结果构建出地电流场强区域指纹库。在150 m×50 m自然环境进行了地电流场强区域指纹库构建实验，结果表明，所构建的0.1 m×0.1 m细粒度地电流场强区域指纹库，平均构建精度为89.84%，最高构建精度为95.46%。

    Abstract:

    The ground current field characterized by field strength is widely applied in fields such as geophysical exploration, seismic monitoring, and through-earth communication. However, due to the variability of regional ground current field strength, it is challenging to establish a regional fingerprint database for ground current field strength. This paper proposes a method for constructing a regional fingerprint database of ground current field strength based on RBFNN. By employing time-division cross-injection to construct a regional ground current field and using orthogonal electrodes to detect ground current field signals at different detection points, fingerprint features of the ground current field strength are extracted. RBFNN is used to fit the field strength variation function model in Kriging interpolation, and Kriging interpolation is then employed to estimate fine-grained fingerprint features of the ground current field strength. Based on the estimation results, a regional fingerprint database of ground current field strength is constructed. An experiment to construct the fingerprint database was conducted in a natural environment of 150 m×50 m. The results show that the constructed fine-grained (0.1 m×0.1 m) regional fingerprint database of ground current field strength achieves an average construction accuracy of 89.84%, with the highest accuracy reaching 95.46%.

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张志诚,苏中,赵辉,李霏,孙振振.基于RBFNN的地电流场强区域指纹库构建方法[J].电子测量技术,2025,48(3):188-196

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  • 在线发布日期: 2025-03-20
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