Acta Geodaetica et Cartographica Sinica ›› 2025, Vol. 54 ›› Issue (9): 1620-1632.doi: 10.11947/j.AGCS.2025.20250137

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An improved Butterworth gravity downward continuation method driven by entropy-PSO dual optimization

Han WANG1,2(), Yun XIAO2,3(), Huaikui GUAN1,2, Weixuan SUN1,2   

  1. 1.School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
    2.National Key Laboratory of Space Reference, Xi'an 710054, China
    3.Xi'an Institute of Surveying and Mapping, Xi'an 710054, China
  • Received:2025-03-31 Revised:2025-08-01 Online:2025-10-10 Published:2025-10-10
  • Contact: Yun XIAO E-mail:wh_021112@163.com;2262164268@qq.com
  • About author:WANG Han (2002—), male, postgraduate, majors in gravitational field data analysis and processing. E-mail: wh_021112@163.com
  • Supported by:
    The National Key Research and Development Program of China(2021YFB3900604);The National Natural Science Foundation of China(42404008);Scientific Innovation Practice Project of Postgraduates of Chang'an University(300103725040)

Abstract:

In response to the challenges of high-frequency noise amplification and instability in downward continuation solutions influenced by gravity, this paper proposes an intelligent continuation method that integrates iterative Butterworth filtering with particle swarm optimization (PSO). The method introduces an improved Butterworth function to reconstruct the downward continuation operator and employs an iterative compensation mechanism to correct spectrum residuals. A particle swarm dual-parameter collaborative optimization method based on information entropy theory is designed to achieve adaptive optimization of the filter's cutoff frequency and order. Furthermore, a fitness feedback-driven dynamic adjustment strategy for inertia weight is proposed to balance global exploration capability and the efficiency of searching for local precise solutions. Experimental results demonstrate that compared to the hybrid domain iterative Tikhonov regularization method and improved derivative iterative method, the proposed method maintains good stability in continuation accuracy under varying noise levels, providing an effective solution for processing marine and aerial gravity data.

Key words: downward extension, wave number domain, Butterworth filter, particle swarm optimization algorithm, iterative approach

CLC Number: