In atomic gravimeter, matter-wave interference of atoms is achieved using a three-pulse sequence to generate atomic interference fringes, and gravitational acceleration is measured by extracting phase information from these fringes. Given the high noise sensitivity of atomic gravimeter interference fringes, traditional fitting methods, including Least Squares (LS) and Extended Kalman Filter (EKF), exhibit limitations in fitting accuracy and stability. With the continuous improvement in measurement precision of gravitational acceleration, enhancing fringe fitting precision becomes particularly crucial. To address this challenge, this study proposes an orthogonal-distance-driven Adaptive Cuckoo Search (ACS) algorithm for interference fringe fitting. The method aims to minimize orthogonal distances through the synergistic integration of dynamic step-size scaling factor adjustment strategy, hybrid Lévy flight distribution parameters, elite disturbance replacement strategy, and nest reset mechanism, significantly improving the global search capability of the cuckoo search algorithm. Validation through both simulated and experimental measurement data demonstrates superior fitting accuracy. After processing ∼46 h of empirical gravitational acceleration data, the ACS-derived mean estimate of gravitational acceleration exhibited minimal residual amplitude relative to theoretical solid Earth tides—approximately 5.0% lower than LS and ∼28.79% lower than EKF. This research validates the effectiveness of the proposed method, providing a novel research framework and solution for atomic gravimeter interference fringe fitting.
Liu et al. (Mon,) studied this question.