| Citation: | LIU Ye, SHI Xing-jian, CAI Zhi-ming, YANG Wen-zhe, LI Hua-wang. Magnetic field reconstruction at test mass using the multi-stage bias correction model[J]. Chinese Optics. doi: 10.37188/CO.2024-0181
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To precisely evaluate the noise from magnetic field and magnetic gradient fluctuations affecting test masses in space gravitational wave detection missions, a Multi-stage Bias Correction Model (MSBCM) is studied for the accurate reconstruction of magnetic fields at test mass. Built upon ensemble learning techniques, the MSBCM employs both standard fully connected neural network modules and residual fully connected neural network modules as weak predictors. Each weak predictor sequentially corrects the prediction biases from the preceding model, cumulatively forming a robust predictive model that achieves precise magnetic field reconstruction at test mass locations. Magnetic field reconstruction experiments conducts on the LISA Pathfinder, eLISA, and Taiji-2 space gravitational wave detection spacecraft, and the proposed MSBCM method demonstrates the lowest mean relative errors along sensitive axes in comparison with other interpolation or estimation methods. In simulating on-orbit experiments, the MSBCM method achieves the root mean square error of magnetic field fluctuations and gradient fluctuations in acceleration noise on the sensitive axis of test mass 1 of 1.68×10−17 (m/s2/Hz1/2) and 4.00×10−17 (m/s2/Hz1/2), respectively. Additionally, MSBCM closely only to the distance weighted method in minimizing the root mean square error for magnetic field fluctuations and gradient acceleration noise on the sensitive axis of test mass 2, records at 1.72×10−16 (m/s2/Hz1/2) and 2.93×10−16 (m/s2/Hz1/2), further validating the advantages of the proposed method in assessing magnetic fields around test masses in space-based gravitational wave detection missions.
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