Low-Earth-Orbit (LEO) satellite Signal-of-Opportunity (SOP) positioning technology has gradually matured to meet the accuracy requirements for unmanned aerial vehicle (UAV) positioning in daily scenarios. Advancements in miniaturization technology for positioning terminals have also made this technology’s application to UAV positioning crucial for UAV development. However, in the increasingly complex electromagnetic environment, there remains a significant risk of degradation in positioning performance for UAVs in LEO satellite SOP positioning due to unintentional or malicious jamming. Furthermore, there is a lack of in-depth research from scholars both domestically and internationally on the anti-jamming capabilities of LEO satellite SOP positioning technology. Due to significant differences in the downlink signal characteristics between LEO satellites and Global Navigation Satellite System (GNSS) signals based on Medium Earth Orbit (MEO) or Geostationary Earth Orbit (GEO) satellites, the anti-jamming research results of traditional satellite navigation systems cannot be directly applied. This study addresses the narrow bandwidth and high signal-to-noise ratio (SNR) characteristics of signals from LEO satellite constellations. We propose a Consecutive Iteration based on Signal Cancellation (SCCI) algorithm, which significantly reduces errors during the model fitting process. Additionally, an adaptive variable convergence factor was designed to simultaneously balance convergence speed and steady-state error during the iteration process. Compared to traditional algorithms, simulation and experimental results demonstrated that the proposed algorithm enhances the effectiveness of jamming threshold settings under narrow bandwidth and high-power conditions. In the context of LEO satellite jamming scenarios, it improves the frequency-domain anti-jamming performance significantly and holds high application value for drone positioning.

Signal-of-Opportunity (SOP) positioning based on Low-Earth-Orbit (LEO) constellations has gradually become a research hotspot. LEO satellite SOP positioning possess strong anti-jamming capabilities due to their large quantity, wide spectral coverage, and high signal power. However, few studies have deeply investigated their anti-jamming performance, particularly regarding the most common interference type faced by ground receivers - Periodic Frequency Modulation (PFM) interference. The downlink signals of LEO satellites differ significantly from those of Global Navigation Satellite Systems (GNSS) based on Medium-Earth-Orbit (MEO) or Geostationary-Earth-Orbit (GEO) satellites, making traditional interference suppression methods inapplicable. In this paper, we utilize the generalized periodicity of PFM interference signals and the characteristics of LEO constellation signals to propose an Adaptive Signal Iterative Projection and Interference Suppression (ASIPIS) algorithm. This algorithm concentrates the energy of PFM interference, which is dispersed over a wide bandwidth, into a few frequency points, enhancing the concentration of the interference and its separation from the LEO satellite signals. This effectively reduces the overlap between LEO satellite signals and interference. The algorithm then uses subspace projection to map the interference and the desired signal into different subspaces, eliminating the interference components and thus reducing the damage to the desired signal during the interference suppression process. Simulations and experiments demonstrate that compared to conventional methods, ASIPIS effectively eliminates single/multi-component PFM interference, improves suppression performance under narrow-bandwidth/high-power conditions, and overcomes limitations of traditional PFM interference suppression approaches for single-antenna LEO signal reception. The significant performance improvement in LEO anti-jamming scenarios against PFM interference confirms the algorithm's value.

In the published article, there was an error in authors order. Instead of "[Lihao Yao, Honglei Qin, Deyong Xian , Boyun Gu, Hai Sha, Gangqiang Guan, Zhijun Liu, Donghan He, Liwei Zhang and Bin Fan]", it should be "[Lihao Yao, Bin Fan, Honglei Qin, Deyong Xian , Boyun Gu, Hai Sha, Gangqiang Guan, Zhijun Liu, Donghan He and Liwei Zhang]".The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.In the published article, the corresponding author name was incorrectly written as "[Lihao Yao, yaolh2202@buaa.edu.cn]". The correct corresponding author name is "[Bin Fan,fb540623907@163.com]".

Signal-of-Opportunity (SOP) positioning based on Low-Earth-Orbit (LEO) constellations has gradually become a research hotspot. Due to their large quantity, wide spectral coverage, and strong signal power, LEO satellite SOP positioning exhibits robust anti-jamming capabilities. However, no in-depth studies have been conducted on their anti-jamming performance, particularly regarding the most common type of interference faced by ground receivers—Periodic Frequency Modulation (PFM) interference. Due to the significant differences in signal characteristics between LEO satellite downlink signals and those of Global Navigation Satellite Systems (GNSSs) based on Medium-Earth-Orbit (MEO) or Geostationary-Earth-Orbit (GEO) satellites, traditional interference suppression techniques cannot be directly applied. This paper proposes a Signal Adaptive Iterative Optimization Resampling (SAIOR) algorithm, which leverages the periodicity of PFM jamming signals and the characteristics of LEO constellation signals. The algorithm enhances the concentration of jamming energy by appropriately resampling the data, thereby reducing the overlap between LEO satellite signals and interference. This approach effectively minimizes the damage to the desired signal during anti-jamming processing. Simulation and experimental results demonstrate that, compared to traditional algorithms, this method can effectively eliminates single/multiple-component PFM interference, improve the interference suppression performance under the conditions of narrow bandwidth and high signal power, and holds a high application value in LEO satellite SOP positioning.