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

doi:10.13474/j.cnki.11-2246.2022.0277

Abstract

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

CLC Number:

P258

YANG Junshan, XIANG Xin, XIONG Xiaofeng, WANG Yanli, LI Xiaoqiang. Adaptive filtering algorithm and its application based on the PPP technique for deformation monitoring in mining area[J]. Bulletin of Surveying and Mapping, 2022, 0(9): 129-133.

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