Presentation Information
[PPS02-P05]In-orbit temperature calibration of the KPLO Magnetometer
*Yesun Ahn1, Ho Jin1, Hyeonhu Park1, Yunho Jang1, Wooin Jo1, Khan-Hyuk Kim1, Seul-Min Baek2 (1.Kyung Hee Univ., 2.Korea Astronomy and Space Science Inst.)
Keywords:
KPLO Magnetometer,fluxgate magnetometer,in-orbit calibration,temperature calibration
The Korea Pathfinder Lunar Orbiter (KPLO), which was launched on August 2022 and currently operating at the lunar orbit, has several scientific payloads and one of them is KPLO Magnetometer (KMAG). The major scientific objectives of KMAG are lunar surface magnetic anomaly investigation and lunar space environment. For the scientific analysis, the observational data should be calibrated by its own proper calibration procedures.
Since the initial operation phase, we have established and applied data processing pipeline. This process includes zero offset determination, orthogonality correction, coordinate transformation, and spacecraft-generated field removal algorithm based on the wavelet transformation. However, there are some residual interference signals remaining uncalibrated during a specific period despite those calibration procedures. These residuals have periodic patterns which have similarity to the variation of the KMAG sensor temperature. In this study, we assume that this remaining noise is related to the temperature change.
To handle these residuals, we conduct in-orbit temperature calibration based on the characteristics of the fluxgate sensors and similarity of overall trends between the measured magnetic field and sensor temperature from KMAG. In this presentation, we present three approaches: (1) local maximum-based approach, (2) relative variation-based approach within a specific time interval, and (3) long-term relationship-based approach. We found that the third method is the most effective in improving the quality of the KMAG dataset across multiple cases. Moreover, this method is validated after applying this approach to the entire dataset and comparing the calibrated results to the ARTEMIS-P1 (THEMIS-B) magnetometer data as a reference. We expect that these results can be employed as a good reference for in-orbit temperature calibration in the future.
Since the initial operation phase, we have established and applied data processing pipeline. This process includes zero offset determination, orthogonality correction, coordinate transformation, and spacecraft-generated field removal algorithm based on the wavelet transformation. However, there are some residual interference signals remaining uncalibrated during a specific period despite those calibration procedures. These residuals have periodic patterns which have similarity to the variation of the KMAG sensor temperature. In this study, we assume that this remaining noise is related to the temperature change.
To handle these residuals, we conduct in-orbit temperature calibration based on the characteristics of the fluxgate sensors and similarity of overall trends between the measured magnetic field and sensor temperature from KMAG. In this presentation, we present three approaches: (1) local maximum-based approach, (2) relative variation-based approach within a specific time interval, and (3) long-term relationship-based approach. We found that the third method is the most effective in improving the quality of the KMAG dataset across multiple cases. Moreover, this method is validated after applying this approach to the entire dataset and comparing the calibrated results to the ARTEMIS-P1 (THEMIS-B) magnetometer data as a reference. We expect that these results can be employed as a good reference for in-orbit temperature calibration in the future.