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一种复杂干扰下捷联惯导纬度自估计方法 被引量:1

A latitude self-estimation method of strapdown inertial navigation under complex interference
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摘要 针对包含角晃动干扰和线运动干扰的复杂环境下捷联惯导纬度自估计问题,提出一种通过对惯性系下重力加速度的二次积分进行多项式拟合,去除干扰后反算重力加速度进行纬度估计的方法,相比传统方法,可最大化两重力矢量夹角,有效提升在复杂线角环境干扰下的纬度估计精度;同时利用重力加速度在初始导航惯性系下北向投影分量符号与纬度符号一致的特点,快速完成纬度正负符号解算。仿真和车载试验表明,高精度光纤捷联惯导可达到0.11°(3σ)/300 s的纬度估计精度。同传统方法相比,所提出方法抗干扰能力更强,更适合工程实用。 Aiming at the latitude self-estimation problem of strapdown inertial navigation system in a complex environment including angular sloshing interference and linear motion interference,a polynomial fitting method is proposed for the quadratic integration of the gravity acceleration in the inertial frame,and the gravity acceleration is inversely calculated after removing the interference.Compared with the traditional method,the estimation method can maximize the angle between the two gravity vectors and effectively improve the accuracy of latitude estimation under the interference of complex line angle environment.At the same time,the sign of latitude is quickly solved by taking advantage of the feature that the sign of the north projection component of the acceleration of gravity in the initial navigation inertial system is consistent with the sign of the latitude.Simulations and on-board tests show that the high-precision fiber-optic strapdown inertial navigation can achieve a latitude estimation accuracy of 0.11°(3σ)/300 s.Compared with the traditional method,the proposed method has stronger anti-interference ability and is more suitable for practical engineering.
作者 宁晓戈 黄继勋 李建勋 NING Xiaoge;HUANG Jixun;LI Jianxun(Department of Automation,School of Electronic Information and Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;Beijing Aerospace Times Optical-Electronic Technology Co.,Ltd.,Beijing 100094,China)
出处 《中国惯性技术学报》 EI CSCD 北大核心 2021年第3期288-292,299,共6页 Journal of Chinese Inertial Technology
基金 国家高技术研究发展计划项目(863-706)(2013AA706503)。
关键词 捷联惯导 纬度估计 复杂干扰 多项式拟合 strapdown inertial navigation system latitude estimation complex interference polynomial optimization
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