## 3 Characteristics of Magnetic Signal  
Before characterizing the magnetic signal acquired from the USV, we first analyzed ground magnetic data for comparison, collected on a beach with low human activity noise near the USV survey area (Figure S2). To understand inherent noise from the magnetometer system, we removed all electronic devices and magnetic materials from the operator's body. Prior to analyzing the characteristics of magnetic signals acquired from the USV, we first collected ground magnetic data from a low-noise beach near the USV survey area for comparison purposes (Figure S2). To understand inherent noise from the magnetometer system, the operator removed all electronic devices and magnetic materials during data collection. Continuous Wavelet Transform (CWT) analysis results from both sensors were compared to identify their performance characteristics, confirming no significant difference in performance, as similar power levels were observed across both sensors. Additionally, strong power was detected in the low-frequency band of 0.001-0.003 Hz, which was identified as the primary geomagnetic signal targeted for analysis in this study. In the Fast Fourier Transform (FFT) and Short-Time Fourier Transform (STFT) analyses, strong signals were consistently observed at 60 Hz, which are considered noise generated by the magnetometer itself. Next, we analyzed the magnetic signals recorded by Sensor 1 and Sensor 2 installed on the USV. Due to their different locations on the USV, the two sensors were affected by distinct noise sources, resulting in clearly distinguishable noise characteristics. To analyze signal characteristics, FFT analysis was performed to identify key frequency components by converting time-domain data to the frequency domain. The results showed that Sensor 2 exhibited generally higher power spectral density across the analyzed spectrum compared to Sensor 1. Furthermore, prominent EMI peaks were observed at approximately 30 Hz and 60 Hz in both sensors, along with common background noise, likely generated by electromagnetic components within the vessel and the magnetometer system (Figure 3a). Figure 2: Schematic illustration of the USV (Parang 5500) showing the installation location of the fluxgate magnetometer (indicated by red dashed line). (**a**) Side view of the USV showing the main magnetic sensor (red dashed line). (**b**) Top view of the USV with the sensor position. The main magnetic sensor was mounted on top of the mast to mitigate magnetic interference from the vessel’s hull and electronic components. To examine the temporal variations of frequency components, STFT analysis was conducted. The results showed that Sensor 1 displayed relatively stable characteristics, featuring a persistent EMI band and weak transient signals. In contrast, Sensor 2, despite being the same sensor model, exhibited highly non-stationary noise with significantly elevated power levels concentrated in the 50-110 Hz band during periods when the vessel performed turning maneuvers (1300-3700 s) (Figure 3b). This strongly suggests the influence of operational noise originating from electrical systems near Sensor 2, particularly the electric motors. For detailed time-frequency analysis, CWT analysis was employed. In the Sensor 1 data, strong signals were consistently observed primarily within the effective signal range  
Figure 3: Frequency and time-frequency analysis (FFT, STFT, CWT) of magnetic data from Sensor 1 and Sensor 2, acquired and collected from the paramagnetic USV. (**a**) Fast Fourier Transform (FFT) spectrum in the frequency domain, showing the amplitude distribution across frequencies up to 125 Hz. The \(y\)-axis represents the amplitude on a logarithmic scale. (**b**) Short-Time Fourier Transform (STFT) spectrogram, illustrating the time-frequency distribution of the magnetic signal during the survey period. The color scale indicates signal intensity in decibels (dB), with red representing higher intensities and blue indicating lower intensities.