Positioning based on Low Earth Orbit (LEO) satellite Signals of Opportunity (SOP) often relies on Doppler observations. Therefore, the accuracy of Doppler frequency measurements significantly impacts the positioning performance. Traditional frequency estimation methods for ORBCOMM satellite signals are typically implemented in the frequency domain and neglect the impact of the “frequency chirp” effect on measurement accuracy, which leads to low computational efficiency, poor noise resistance, and limited estimation accuracy. To address this issue, a high-precision frequency estimation method combining a “coarse and fine” process is proposed. In the coarse estimation process, ephemeris prior information is combined with matched filtering to effectively separate the Doppler rate, thereby mitigating the spectral broadening caused by the Doppler rate. In the fine estimation process, ORBCOMM signal characteristics are fully exploited. Single-sideband filtering is applied to improve noise resistance, followed by precise frequency discrimination of the delayed signal. Experimental results demonstrate that the proposed method outperforms the state-of-the-art “FFT + MLE” approach, achieving a frequency measurement accuracy on the order of 0.01 Hz while requiring fewer computational resources. Furthermore, this method improves estimation performance by approximately 12 dB without compromising frequency measurement accuracy.