<p>In X-ray pulsar-based navigation, phase and Doppler frequency estimation based on the maximum likelihood estimation and grid search methods is widely used in practical missions and theoretical analysis. However, due to the non-convexity of the objective function and the inefficiency of the grid search method, a key challenge is how to achieve fast estimation of phase and Doppler frequency while maintaining accuracy. To address this issue, the fast and high-precision estimation of phase and Doppler frequency based on prior information and non-convex optimization is proposed in this paper. First, leveraging the prior state information of the spacecraft, an enhanced on-orbit phase model is established by considering a reference time at any given moment. Then, the statistical properties of the parameters to be estimated are analyzed, and the corresponding prior probability model is constructed, using the Bayesian estimation model as the objective function. Finally, incorporating non-convex optimization theory, the Nesterov-adaptive moment estimation is employed to automatically adjust the step size of the quasi-Newton algorithm. Simulation and experimental results demonstrate that the proposed method achieves rapid convergence with high precision, effectively balancing real-time performance and estimation accuracy compared to traditional phase and Doppler frequency estimation methods. Using the Crab pulsar as the primary case study, when the observation duration is 1800 s and the detector area is 30 cm², the proposed method reduces the running time by 99.91% and 73.68% compared to the traditional grid search and adaptive grid search methods, respectively. Moreover, the proposed method yields positioning errors below 10 km under rapid estimation conditions.</p>