Fang Ke, Cai Tijing
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China.
Sensors (Basel). 2024 Sep 11;24(18):5899. doi: 10.3390/s24185899.
Attitude errors, accelerometer bias, the gravity disturbance vector, and their coupling are the primary factors obstructing strapdown airborne vector gravimetry. This paper takes the geocentric inertial frame as a reference and solves the kinematic equations of its motion and its errors of the body frame and local geographic frame in the Lie group, respectively; the attitude accuracy is improved through a high-precision navigation algorithm. The constant accelerometer bias is estimated through Kalman filtering and is deducted from the accelerometer output to eliminate its influence. Based on the EGM2008 model, the low-frequency components of the gravity disturbance vector are corrected. The gravity disturbance vectors after model data fusion were low-pass filtered to obtain the ultimate results. This method was applied to flight experimental data in the South China Sea, and a gravity anomaly accuracy of better than 0.5 mGal, a northward gravity disturbance accuracy of 0.85 mGal, and an eastward gravity disturbance accuracy of 4.0 mGal were obtained, with a spatial resolution of approximately 4.8 km.
姿态误差、加速度计偏差、重力扰动矢量及其耦合是阻碍捷联式航空矢量重力测量的主要因素。本文以地心惯性系为参考，分别在李群中求解其运动的运动学方程以及机体坐标系和当地地理坐标系的误差；通过高精度导航算法提高姿态精度。通过卡尔曼滤波估计加速度计的常值偏差，并从加速度计输出中扣除以消除其影响。基于EGM2008模型，对重力扰动矢量的低频分量进行校正。对模型数据融合后的重力扰动矢量进行低通滤波以获得最终结果。该方法应用于南海飞行实验数据，获得了优于0.5 mGal的重力异常精度、0.85 mGal的北向重力扰动精度和4.0 mGal的东向重力扰动精度，空间分辨率约为4.8 km。
