A GNSS/INS Integrated Navigation Algorithm Based on Kalman Filter

Q3 Engineering

IFAC-PapersOnLine Pub Date : 2018-01-01 DOI:10.1016/j.ifacol.2018.08.151

Guangqi Wang , Yu Han , Jian Chen , Shubo Wang , Zichao Zhang , Nannan Du , Yongjun Zheng

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引用次数: 24

Abstract

GNSS/INS (Global Navigation Satellite System/ Inertial Navigation System) integrated navigation system can be applied to agricultural UAV (unmanned aerial vehicle) with the following two requirements: (1) After working for a long time, the precision of navigation parameters will not decrease; (2) The integrated navigation algorithm is simple and reliable, which requires low processing capacity for airborne chips. Aiming at satisfying above two requirements, firstly, the centralized Kalman filter method is used to fuse GPS (Global Position System) and INS systems under the premise of loose coupling. The combination is compact, which greatly reduces the amount of computing in the system and simplifies the complexity of the system. Secondly, the error of INS system navigation parameters estimated by discrete Kalman filter algorithm is fed back into INS system by feedback emendation method, which overcomes the problem that the navigation accuracy will decline after long time work. Finally, the simulations of velocity and position error after filtering are demonstrated respectively. The stability and effectiveness of proposed algorithms are verified.

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基于卡尔曼滤波的GNSS/INS组合导航算法

GNSS/INS(全球导航卫星系统/惯性导航系统)组合导航系统可应用于农用无人机，有以下两个要求:(1)在长时间工作后，导航参数的精度不会降低;(2)组合导航算法简单可靠，对机载芯片的处理能力要求较低。针对上述两个要求，首先，在松耦合的前提下，采用集中卡尔曼滤波方法对GPS (Global Position System)和INS系统进行融合。这种组合结构紧凑，大大减少了系统的计算量，简化了系统的复杂性。其次，将离散卡尔曼滤波算法估计的惯导系统导航参数误差通过反馈修正方法反馈到惯导系统中，克服了惯导系统长时间工作后导航精度下降的问题;最后分别对滤波后的速度误差和位置误差进行了仿真。验证了所提算法的稳定性和有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IFAC-PapersOnLine Engineering-Control and Systems Engineering

CiteScore

1.70

自引率

0.00%

发文量

1122

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