一种水下用改进互补滤波结合Kalman滤波联合修正算法

A Joint Modified Algorithm Combined with Improved Complementary Filtering and Kalman Filtering for Underwater Use

针对惯导系统器件自身及初始姿态阵的残留误差在导航定位解算过程中,会随着时间推移而产生累积效应,对导航定位精度产生严重影响,提出一种水下用改进互补滤波结合Kalman滤波联合修正算法。该算法结合了实际水下机动特性,采用平滑滤波及IMU输出模值联合对机动状态进行判定,采用基于PID的改进互补滤波,结合Kalman滤波在线修正算法,在定常运动段对误差进行估计修正。该算法适用于实际水下工作环境、动态响应速度快、稳态误差小,提高了水下导航定位精度。相应仿真实验验证了该算法的正确性及有效性。

Aiming at the accumulation effect of residual errors of inertial navigation system components and initial attitude array in the process of navigation and positioning calculation, which has serious influence on navigation and positioning accuracy, a joint modified algorithm combined with improved complementary filtering and Kalman filtering for underwater use is proposed. The algorithm combines the actual underwater maneuvering characteristics, uses smoothing filter and IMU output modulus to determine the maneuvering state, uses improved complementary filter based on PID, and combines Kalman filer online modified algorithm to estimate and correct the errors in the steady motion segment. The algorithm is suitable for actual underwater working environment, has fast dynamic response and small steady-state error, and improves the accuracy of underwater navigation and positioning. Corresponding simulation experiments verify the correctness and effectiveness of the algorithm.