中国空间科学技术

中国空间科学技术 ›› 2021, Vol. 41 ›› Issue (4): 77-84.doi: 10.16708/j.cnki.1000-758X.2021.0053

• 论文 • 上一篇    下一篇

一种多传感器组合导航系统的改进异步融合算法

刘丽丽，林雪原，陈祥光   

  1. 1.烟台南山学院电气与电子工程系，烟台265713
    2.北京理工大学，北京100081
  • 出版日期:2021-08-25 发布日期:2021-07-30
  • 基金资助:
    国家自然科学基金（60874112，61673208）；烟台市“双百计划”人才项目（YT201803）

An improved asynchronous fusion algorithm for multisensor integrated navigation system

LIU Lili，LIN Xueyuan，CHEN Xiangguang   

  1. 1.Department of Electrical and Electronic Engineering, Yantai Nanshan University, Yantai 265713, China
    2.Beijing Institute of Technology, Beijing 100081, China
  • Published:2021-08-25 Online:2021-07-30

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摘要： 针对多传感器组合导航系统中各子导航传感器数据采样率不同且呈有理数倍的这一特殊问题，提出了一种组合导航系统的信息融合算法。首先将多传感器组合导航系统的原始状态方程变换成状态数据块向量与当前状态向量之间的关系，进而构成新的状态方程，而原始量测方程表达为与状态数据块向量之间的关系，进而构成新的量测方程。然后基于具有尺度与小波特性的矩阵算子，给出了改进异步融合算法的具体实现步骤。最后将该算法应用于CNS/GNSS/SINS/高度表多传感器组合导航系统。仿真结果表明，相对于传统算法，位置、速度和姿态精度可分别提高约20%、15%和10%，验证了本算法的高精度特性和可行性。

关键词: 异步融合, 状态数据块向量, 多传感器组合导航系统, 多尺度

Abstract: In order to solve the problem that the data sampling rate of each subnavigation sensor in the multi-sensor integrated navigation system is different and rational, an information fusion algorithm for the integrated navigation system was proposed. First, the original state equation of the multi-sensor integrated navigation system was transformed into the relationship between the state data block vector and the current state vector to form a new state equation, and the original measurement equation was expressed as the relationship between the state data block vector to form a new measurement equation. Then, based on the matrix operator with scale and small baud property, the concrete implementation process of the improved asynchronous fusion algorithm was given. Finally, the algorithm was applied to the multisensor integrated navigation system of CNS/GNSS/SINS/altimeter. The simulation results show that the position, speed and attitude accuracy can be improved by about 20%, 15% and 10% respectively, compared with the traditional algorithm. The high-precision characteristics and feasibility of the algorithm are verified.

Key words: asynchronous fusion, state data block vector, multi-sensor integrated navigation system, multi-scale