## 1 Introduction
According to the processing domain, approaches can be divided into time domain and frequency domain anti-jamming algorithms. The antenna array anti-jamming technology uses multiple antenna elements. According to the different incident directions of the signal and jamming, interference cancellation is performed using vector weighting, mainly using spatial domain anti-jamming algorithms [24; 25; 26; 27; 28; 29; 30; 31; 32; 33]. Compared with antenna arrays, single antennas are widely used in the drone field due to their small size, low cost, and low power consumption. The single-antenna time-frequency domain anti-jamming algorithm is based on the premise that the navigation signal is much weaker than the noise. It assumes that the power spectrum of the superimposed signal and noise is flat and that the spectral lines at different frequencies follow the same distribution. It then calculates the interference detection threshold for anti-jamming processing. In a scenario with strong signals, however, the statistical characteristics of the spectral lines at different frequencies are correlated with the frequency due to the presence of strong signals. This requires different interference detection thresholds for the same false alarm probability, leading to a higher false alarm probability or lower detection probability, rendering the anti-jamming algorithm ineffective [34; 35]. Conventional anti-jamming methods cannot be directly applied due to the distinct characteristics of LEO satellite signals, such as a high ground SNR (typically ranging from 15-30 dB) and narrow downlink bandwidths, which significantly differ from traditional satellite navigation signals. This issue is particularly challenging in the context of time-frequency domain anti-jamming scenarios, widely used in UAV applications with single-antenna receivers. For scenarios with high SNRs and strong signals, most traditional research has focused on spatial domain anti-jamming algorithms using antenna array techniques [34; 35; 36; 37; 38; 39; 40]. However, there is limited research on time-frequency domain anti-jamming algorithms applicable to single-antenna receivers due to the presence of strong signals, which significantly affect jamming threshold settings and lead to high false alarm rates or low detection probabilities. Currently, only two studies in the literature mention frequency domain anti-jamming algorithms suitable for strong signal scenarios [34; 35]. One of them, the Anti-Jamming Weighting Generation (AJWG) algorithm [34], optimizes the equivalent carrier-to-noise ratio (CNR) at the despread output for each spectral line of the signal, deciding whether the signal's single spectral line is jamming before subsequently eliminating or preserving it. Due to the excessively large computational complexity of the AJWG algorithm, it is rarely used in engineering applications. Therefore, this paper does not further analyze the AJWG algorithm. This study conducted research on single-antenna anti-jamming technology for LEO satellite SOP positioning. Firstly, the other GNSS frequency domain anti-jamming improvement algorithm was analyzed, revealing several flaws when directly applied to the anti-jamming scenario in UAVs using LEO satellite SOP positioning. Secondly, considering the narrow downlink bandwidth and high ground SNR characteristics of LEO satellite constellation signals, a Consecutive Iteration based on Signal Cancellation (SCCI) algorithm was proposed, which significantly reduces the errors generated during the model fitting process. Additionally, an adaptive variable convergence factor was designed to address the challenge of balancing convergence speed and steady-state error during iterations. Finally, to verify the jamming suppression performance of the proposed algorithm, simulations and experimental validations were conducted in different scenarios.