基于自适应高斯渐进滤波的工程车GNSS/INS紧组合定位OA北大核心CSTPCD
GNSS/INS Tightly Coupled Positioning of Engineering Vehicle Based on Adaptive Gaussian Progressive Filter
研究了量测野值影响下的工程车GNSS/INS紧组合定位问题,提出了一种基于自适应高斯渐进滤波的车辆定位方法.首先,为降低量测野值对滤波器的破坏风险,利用假设检验方法对量测野值进行检测和剔除;其次,对于野值漏检测引起的定位性能下降的问题,设计了自适应的高斯渐进滤波方法来补偿量测的不确定性;特别地,利用线性化误差与系统估计误差的变化关系,对渐进量测更新方式进行了改进,从而实现对线性化误差的间接补偿.最后,通过工程车GNSS/INS紧组合定位实验进行结果分析,验证了所提方法的可靠性和优越性.
The GNSS/INS tightly coupled location problem of engineering vehicle under the influence of measurement outliers is stud-ied,and a vehicle location method based on adaptive Gaussian progressive filtering is proposed.Firstly,in order to reduce the risk of fil-ter damage caused by measured outliers,the hypothesis testing method is used to detect and eliminate measurement outliers.Secondly,an adaptive Gaussian progressive filtering method is designed to compensate the uncertainty of measurement for the degradation of posi-tioning performance caused by outliers.In particular,by using the relationship between the linearization error and the system estimation error,the progressive measurement update method is improved,so as to realize the indirect compensation of the linearization error.Final-ly,the reliability and superiority of the proposed method are verified through GNSS/INS tightly coupled positioning experiment.
张文安;沈嘉俊;史秀纺;杨旭升;王军
浙江工业大学信息工程学院,浙江 杭州 310023中电海康集团有限公司,浙江 杭州 310023
计算机与自动化
GNSS/INS紧组合工程车量测野值高斯渐进
GNSS/INS tightly coupledengineering vehiclemeasurement outliersGaussian progressive
《传感技术学报》 2024 (004)
620-628 / 9
浙江省自然科学基金项目(LY23F030006);国家自然科学基金项目(62173305)
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