# Automatic Detection of Quasi-Periodic Emissions from Satellite Observations by Using DETR Method
## 2 Dataset and Target
### Identification and Characteristics of QP Emissions  
Figure 1 shows one example event of a QP wave recorded by the CSES-01, by presenting the power spectral density (PSD) values of the magnetic field (Figure 1a) and the electric field (Figure 1b), respectively. It is seen that the frequency of this QP event varied from the \(f_{\mathrm{cp}}\) to approximately 1.8 kHz. The intensity of the QP structure gradually decreased from high to low latitudes, but the modulation period remained relatively stable. The discrete spectral lines are visible, but the period between two neighboring wave elements is not fixed and slightly varies. The red line is the local proton gyrofrequency frequency \(f_{\mathrm{cp}}\), which is computed by the following equation:  
\[f_{\mathrm{cp}}=\frac{qB}{m} \tag{1}\]where \(q\) is the proton charge, \(m\) is the mass of the proton, and \(B\) is the total geomagnetic field data, which were provided from the HPM onboard the CSES-01. The QP emissions can be classified into five different types based on their morphological characteristics in the spectrogram: the rising tone type (see Figure 2a), falling tone type (see Figure 2b), burst type (see Figure 2c), non-dispersive type (see Figure 2d), and hybrid type (mixture of rising and falling types) [22]. The rising tone type is the most commonly observed, and the slope of each wave package increases with time, illustrating a short arc pattern. The falling tone type is the opposite of the rising tone, and the slope of each QP element decreases with time. The hybrid type presents both rising and falling tone structures. The burst type is composed of elements with a strong burst of discrete emission and a weak diffuse emission. There  
Figure 1: An example of a QP wave event recorded by the CSES-01 on 6 January 2019, from 08:50 to 9:25 UTC, presented via the PSD values of the magnetic field (**a**) and electric field (**b**). The proton cyclotron frequency is represented by the red lines. Figure 2: The different types of QP waves recorded by the CSES-01 in the ionosphere; (**a**) rising tone type, (**b**) falling tone type, (**c**) burst type, (**d**) non-dispersive type. will be a clear split in this type of element. The non-dispersive type has no clear distinction between the QP elements, its intensity gradually decreases from higher to lower latitudes, and the intensity decreases gradually from the cut-off frequency to the maximum frequency. For most QP emissions of all types, with decreasing latitude, the bandwidth of QP emissions decreases, with a more pronounced decrease at the maximum frequency and a less pronounced decrease at the cut-off frequency. Considering that the observations from EFD are more prominent than those from SCM, this study specifically focuses on the utilization of EFD data. Firstly, we plotted the spectral image (PSD value) of the electric field in the ELF frequency range for each set of orbit data spanning a period of five years from January 2019 to May 2023. Secondly, we used the manual detection method to identify the QP wave phenomena in the ELF frequency range; a total of 1765 orbits' data containing QP waves were selected from the extensive dataset. In the analysis of the 1765 QP events, we found that QP events predominately appeared within the latitude ranges of \(-69^{\circ}\) to \(-28^{\circ}\) and \(28^{\circ}\) to \(69^{\circ}\) and preferably occurred during the main and recovery phases of the storm, which is consistent with the statistical analysis of [PERSON] et al. based on long-term observations from the DETMETER satellite [23]. In in the equatorial region, electric field observation is heavily interfered with by artificial noise from EFD or the satellite internal communication design [17]. Thus, to avoid the high noise and to obtain reliable QP data, we mainly truncated the orbit data within the latitude ranges of \(-69^{\circ}\) to \(-28^{\circ}\) and \(28^{\circ}\) to \(69^{\circ}\) to build a dataset for training (see Figure 3). In total, we obtained approximately 3000 QP data samples.