测绘通报 ›› 2022, Vol. 0 ›› Issue (9): 129-133.doi: 10.13474/j.cnki.11-2246.2022.0277

• 技术交流 • 上一篇    下一篇

矿区地表形变PPP监测自适应滤波算法及其应用

杨俊山1,2, 项鑫1,2, 熊晓峰1,2, 王艳利1,2, 李小强3   

  1. 1. 河南省地球物理空间信息研究院, 河南 郑州 450000;
    2. 河南省地质物探工程技术研究中心, 河南 郑州 450000;
    3. 郑州铁路职业技术学院, 河南 郑州 450000
  • 收稿日期:2022-07-11 发布日期:2022-09-30
  • 作者简介:杨俊山(1988—),男,工程师,主要从事测绘地理信息、多测合一、自然资源调查监测等方面的研究。E-mail:448084794@qq.com
  • 基金资助:
    国家自然科学基金(42074045)

Adaptive filtering algorithm and its application based on the PPP technique for deformation monitoring in mining area

YANG Junshan1,2, XIANG Xin1,2, XIONG Xiaofeng1,2, WANG Yanli1,2, LI Xiaoqiang3   

  1. 1. Henan Provincial Institute of Geophysical Spatial Information, Zhengzhou 450000, China;
    2. Henan Engineering Technology Research Center for Geophysical Prospecting, Zhengzhou 450000, China;
    3. Zhengzhou Railway Vocational & Technical College, Zhengzhou 450000, China
  • Received:2022-07-11 Published:2022-09-30

摘要: 矿区地表易发生开裂、移动、塌陷等灾害,对矿区人文及生态环境造成巨大破坏。因此,针对矿区地表的监测研究意义重大。然而,常规的监测数据解算方法精度依赖于先验模型参数的准确性,若模型参数不准确,则解算精度难以满足监测需求。鉴于此,本文提出了基于PPP的矿区地表形变监测自适应滤波算法,并利用矿区工程数据进行试验,验证了算法的优越性。结果表明,本文算法能有效地控制动态模型参数偏差的影响,提高监测数据解算的稳定性,相比传统滤波算法,能够有效提高解算精度。

关键词: PPP, 矿区, 形变监测, 自适应滤波

Abstract: The surface of the mining area is prone to cracking, movement, collapse and other disasters, causing great damage to the human and ecological environment of the mining area. Therefore, it is of great significance to study the surface monitoring in mining area. However, the accuracy of conventional filtering methods depends on the accuracy of prior model parameters. If the model parameters are not exact, the accuracy is difficult to meet the monitoring requirements. In view of this, an adaptive filtering algorithm for deformation monitoring in mining area based on the precise point positioning (PPP) technique is proposed, and the data collected in engineering practice of mining area is applied to carry out the practical experiments, then the superiority of the algorithm is verified. Results show that the proposed algorithm can effectively control the influence of dynamic model parameter deviation and improve the stability of monitoring data calculation. Meanwhile, the calculation accuracy is improved compared with the traditional filtering algorithm.

Key words: PPP, mining area, deformation monitoring, adaptive filtering

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