It is widely distributed across the frequency bands of LEO satellites SOP signals [25; 26; 27]. Previous research on suppressing PFM interference has primarily focused on GNSSs and similar systems. The general approach involves leveraging differences between GNSS signals and interference in the time-frequency domain, spatial domain, or spatiotemporal domain to propose corresponding interference suppression methods [28; 29]. Among these, spatial-temporal joint processing using the spatial resolution of antenna arrays at the receiver end can effectively suppress various types of interference. However, considering the high hardware cost and complexity of the terminal, this method has limited applicability. In contrast, single antennas are widely used due to their smaller size, lower cost, and reduced power consumption compared to antenna arrays. Therefore, the development of detection and suppression methods for PFM interference suitable for single-antenna receivers remains a research hotspot. Currently, the most effective approach involves transforming the received signal into the time-frequency domain for interference detection. Based on the characteristics of energy distribution in the time-frequency domain after transformation, typical time-frequency analysis methods include the Short-Time Fourier Transform (STFT) [30], Wavelet Packet Transform (WPT) [31; 32], and Fractional Fourier Transform (FrFT) [33]. However, the STFT cannot effectively accumulate signal energy and suffers from insufficient resolution due to its fixed window width. Discrete WPT tends to cause spectrum aliasing and amplitude distortion. Additionally, the non-orthogonality of discrete FrFT can distort the desired signal, and its effectiveness is primarily limited to linear frequency modulation (LFM) interference. Most importantly, while these methods have some capacity to suppress frequency-modulated (FM) interference, the significant overlap between the interference and the desired signal in the time-frequency or FrFT domain inevitably leads to substantial damage to the desired signal when interference is removed. This issue is further exacerbated by advancements in electronic technology in recent years, where modern small-scale jammers can produce interference containing multiple FM components, increasing the degree of damage to the desired signal during interference suppression. Such interference suppression processes may result in signal quality loss that is tolerable when dealing with GNSS signals that typically have downlink bandwidths of several tens of MHz. However, for LEO satellite signals, which generally have much narrower downlink bandwidths (e.g., 500 kHz for the Iridium system and only 25 kHz for the Orbcom system), the damage to signal quality caused by interference suppression can significantly impact the subsequent positioning accuracy. Therefore, directly applying traditional time-frequency-based interference suppression methods to LEO satellite PFM interference scenarios yields suboptimal results. This paper proposes a Signal Adaptive Iterative Optimization Resampling (SAIOR) algorithm, leveraging the characteristics of PFM interference signals and LEO satellite signals. This algorithm concentrates the energy of PFM interference, which is originally dispersed over a wide bandwidth, into a few frequency points in the newly sampled data through appropriate secondary sampling. This enhances the aggregation of interference, effectively reducing the overlap between the LEO satellite signal and interference, thereby minimizing the damage to the desired signal during the anti-jamming process. Simulations and experiments validate the performance improvements of the algorithm. The results demonstrate that this method effectively eliminates single/multi-component PFM interference while causing minimal damage to SOP signals, making it suitable for high-precision positioning receivers.