上海交通大学学报

上海交通大学学报 >

2022 , Vol. 56 >Issue 11: 1447 - 1452

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2022.167

制导、导航与控制

基于PF-UKF组合滤波的SINS/GPS组合导航系统空中对准方法

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  • 扬州大学 信息工程学院,江苏 扬州 225127
高红莲(1997-),女,贵州省六盘水市人,硕士生,现主要从事惯性组合导航系统研究.

收稿日期: 2022-05-16

  网络出版日期: 2022-07-11

基金资助

国家自然科学基金(61873346);扬州大学“青蓝工程”资助项目

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In-Flight Alignment Method of Integrated SINS/GPS Navigation System Based on Combined PF-UKF Filter

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  • College of Information Engineering, Yangzhou University, Yangzhou 225127, Jiangsu, China

Received date: 2022-05-16

  Online published: 2022-07-11

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摘要

针对捷联式惯性导航系统(SINS)/全球定位系统(GPS)组合导航系统模型的误差以及粒子滤波(PF)存在的粒子退化问题,结合无迹卡尔曼滤波(UKF)算法,提出一种基于PF-UKF组合滤波的SINS/GPS组合导航系统空中对准方法.由误差四元数代替姿态角,以SINS和GPS的位置差和速度差作为观测量,建立新的组合导航系统误差方程.所提出的PF-UKF组合滤波算法将采样粒子分为随机粒子和确定粒子,其中随机粒子为概率密度函数所采集,确定粒子为UKF中采集Sigma点后所求取的系统状态值.由此降低了PF处理粒子时的复杂程度以及粒子退化的程度.仿真结果表明:相比于UKF算法,该方法有效提高了组合导航系统的精度,具有较好的鲁棒性.

关键词： 组合导航; 无迹卡尔曼滤波; 粒子滤波; 四元数

本文引用格式

高红莲, 尤杰, 曹松银 . 基于PF-UKF组合滤波的SINS/GPS组合导航系统空中对准方法[J]. 上海交通大学学报, 2022 , 56(11) : 1447 -1452 . DOI: 10.16183/j.cnki.jsjtu.2022.167

Abstract

Aimed at the modeling error of the integrated strapdown inertial navigation system(SINS)/global positioning system (GPS) navigation system and the particle degradation problem of particle filter(PF), an in-flight alignment method of integrated SINS/GPS navigation system based on the combined PF-UKF filter is proposed, in combiation with the unscented Kalman filter(UKF). First, the attitude angle is replaced by the error quaternion. The position and velocity differences between SINS and GPS are selected as the observation variables. In addition, a novel error equation of the integrated navigation system is established. Moreover, the sampled particles are divided into random particles and deterministic particles in the proposed combined PF-UKF filter. The random particles are collected by probability density function, and the determined particles are the state values obtained by collecting sigma point of UKF algorithm. Therefore, the proposed method can effectively reduce the complexity of PF and the degree of particle degradation. The simulation results show that compared with the UKF algorithm, the proposed method can effectively improve the error accuracy of integrated navigation system with a better robustness.

Key words： integrated navigation; unscented Kalman filter (UKF); particle filter (PF); quaternion

参考文献

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