## 7 Conclusions  
In this paper, we first propose a wideband flexible monitoring algorithm based on resampling filtering, which adaptively adjusts the receiver sampling rate to four times the signal bandwidth for low-orbit satellite wideband OFDM signals, thereby improving analysis sensitivity. Secondly, we introduce an algorithm for Doppler frequency offset estimation based on satellite ephemeris and coordinate system transformation, which achieves the high-precision estimation of Doppler frequency offsets in the dynamic channel  
Figure 10: OFDM subcarrier modulation scheme identification accuracy.  
of low-orbit satellites, thereby mitigating the impact of channel dynamics on OFDM signal analysis and identification. Finally, we present a detection, analysis, and identification algorithm based on intrinsic features of OFDM signals. Initially, the OFDM signal is differentiated from single-carrier signals using the cumulative feature of OFDM signals. Subsequently, the algorithm estimates parameters such as symbol length, CP length, the number of subcarriers, and the oversampling rate using the cyclic transformation domain feature of OFDM signal CP. After removing the cyclic prefix, the algorithm extracts each subcarrier of the OFDM signal and jointly identifies the modulation schemes of these subcarriers based on their multi-domain intrinsic features. The simulation experiment conducted on OFDM signal detection under the presence of delay and Doppler in an AWGN channel shows that the low-orbit satellite broadband OFDM signal monitoring method proposed in this paper can accurately detect OFDM signals in the absence of prior information and differentiate them from single-carrier signals. The detection accuracy can reach over 90% at SNR \(\geq\) 2 dB. Additionally, the proposed method can reliably identify the structural parameters of OFDM signals. When the number of accumulated symbols exceeds 10, some parameters can achieve a 100% correct rate. Finally, the method can recognize the modulation schemes of each subcarrier. At SNR \(\geq\) 7 dB, the average identification rate can reach over 90%.  
All analyses and assumptions presented in this paper are predicated on the intact structure of the CP-OFDM signals, which possess cyclostationary characteristics. However, due to the complex dynamic nature of LEO satellite channels, these cyclic properties may be compromised during transmission. Consequently, confining the analysis to cyclic symbols can result in a loss of degrees of freedom. Therefore, the application of conjugate cyclic statistics and widely-linear signal processing methods can be employed to analyze non-cyclic symbols, thereby enhancing system performance.  
[PERSON] designed the study and developed the methodology. [PERSON] collected the data and conducted experiments. [PERSON] and [PERSON] prepared the initial draft of the manuscript. [PERSON] contributed to both the theoretical derivation and the experimental design. [PERSON], [PERSON] and [PERSON] reviewed and revised the manuscript. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Key Research and Development Program of China under Grant 2022 YFC3301404, and in part by the Young Elite Scientists Sponsorship Program by CAST under Grant 2022 QNRC001.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
Authors [PERSON] and [PERSON] were employed by the company CETC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.