## 1 Introduction  
Global navigation satellite system (GNSS) is currently widely used in both military and civilian fields [1, 2]. It is extremely important to keep this system free of interference. Types of interference with GNSS include multipath [3, 4], ionospheric scintillation [5], spoofing [6, 7], electromagnetic interference, satellite signal anomalies, and intense L-band solar radio bursts (SRBs) [8]. SRB is a strong signal in the microwave band from solar plasma radiation and cyclotron synchrotron radiation. The entire radiation bandwidth extends from the millimeter to the kilometer wave band. L-band SRB (1415 MHz) interferes with the GNSS signal most significantly due to the fact that it is close to GNSS frequencies, such as GPS (L1: 1575.42 MHz, L2: 1227.60 MHz, L5: 1176.45 MHz), GLONASS (G1: 1602 MHz, G2: 1246 MHz) and Galileo (E1: 1575.42 MHz, E5: 1191.795 MHz). Strong radio noise can cause the carrier-to-noise ratio (\(C/N_{0}\)) of a GNSS receiver to decrease, which directly affects the tracking and acquisition of the GNSS signal. In worse interference cases, cycle slip, loss of lock, interruption and other phenomena may occur [9]. Researchers have studied the impact of SRB on GNSS since 2005. [PERSON] et al. [10] analyzed the phenomenon of GPS loss of lock due to a SRB event on 28 October 2003. They pointed out that the flux density threshold of the solar radio bursts affecting GPS signals is between 4000 and 12,000 solar flux unit (SFU). [PERSON] et al. [11] analyzed the effects of several SRB events in December 2006 on the \(C/N_{0}\) of GPS and found a strong correlation between \(C/N_{0}\) and solar radio emission power. Through theoretical analysis, [PERSON] et al. [12] found that SRBs with emission power of 1000 SFU or higher may lead to GPS or GLONASS tracking faults. The effect is especially prevalent at the L2 frequency, which is lower than the threshold proposed by [PERSON] et al. [10]. [PERSON] et al. [13] analyzed the influence of SRBs on GPS \(C/N_{0}\) and concluded that the threshold value of solar radio burst effects on GNSS is approximately 1807 SFU. [PERSON] et al. [14; 15] studied the impact of the SRB event on 24 September 2011 on a single-point precise positioning service and the performance of GNSS receivers. Subsequently, [PERSON] et al. [16] studied the event with higher sampling GPS data and evaluated the impact of SRBs on GPS signal characteristics, including the signal-to-noise ratio, loss of lock, and phase tracking. The study of [17] shows that SRBs are not limited to the vicinity of sunspot maxima. [PERSON] et al. [18] specifically analyzed the influence of a SRB event on 13 December 2006 on GNSS performance and positioning error in several regions in China. The effects of the SRB event on 6 September 2017 on GNSS signals and the corresponding response of the ionosphere were studied in [19; 20; 21; 22]. Recently, a number of automatic detection and classification methods for SRBs have been proposed. [PERSON] et al. [23] proposed a multimodal deep learning method for SRB classification. An autoencoder (AE) together with structured regularization was used to enforce and learn the modality-specific sparsity and density of each modality. The proposed network can effectively learn the representation of the solar radio spectrum. Subsequently, [PERSON] et al. [24] utilized a convolutional neural network (CNN) for the classification of solar radio spectra and obtained better experimental results than [PERSON] et al. [23]. [PERSON] et al. [25; 26] designed an event recognition-analysis system that can automatically detect solar type III radio bursts and mine burst information from the dynamic spectra observed by the Nancay Decameter Array (NDA). [PERSON] et al. [8] proposed an automated method to detect SRBs. Although the method does not classify the types of radio bursts, it is able to discriminate between dynamic spectra with and without SRBs.