GNSS/MIMU tightly coupled integrated with improved multi-state ZUPT/DZUPT constraints for a Land vehicle in GNSS-denied enviroments

Ning, Yipeng; Sang, Wengang; Yao, Guangchun; Bi, Jingxue; Wang, Shida

doi:10.1080/19479832.2020.1829718

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Two criteria can be used to describe the performance of the detection method: the precision of the method, which can be calculated by (5):…”

Section: Definition Of Zero-velocity Detectionmentioning

confidence: 99%

“…However, errors in the INS will accumulate with time due to the integral characteristics of the dead reckoning algorithm. For a vehicle-mounted INS, zero-velocity update (ZUPT) technology [4][5][6] is a convenient * Author to whom any correspondence should be addressed. method of suppressing the divergence of navigation errors and improving the navigation accuracy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A zero-velocity update method based on neural network and Kalman filter for vehicle-mounted inertial navigation system

Li¹,

Li²,

Liang³

2023

Meas. Sci. Technol.

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Zero velocity Update (ZUPT) is an effective method to restrain the error divergence of the Inertial Navigation System (INS). Right detection of zero velocity points and appropriate filtering algorithm are the key factors for the success of ZUPT. In this paper, a ZUPT method for vehicle mounted INS based on neural network and Kalman Filter is proposed. The efficiency and accuracy of the zero velocity detection is improved by neural network. The precision of the proposed method can reach 99.19%, and the recall rate is improved by 24% compared with the method based on SVM. And this method has similar accuracy and better real-time performance with the method based on LSTM. Based on the zero velocity detection by neural network, the navigation error is estimated and compensated by Kalman Filter. The effectiveness of the proposed method is proved by vehicular experiment which shows that the velocity error is reduced to 24.2% and the position error is reduced to 9.5%.

show abstract

“…Two criteria can be used to describe the performance of the detection method: the precision of the method, which can be calculated by (5):…”

Section: Definition Of Zero-velocity Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A zero-velocity update method based on neural network and Kalman filter for vehicle-mounted inertial navigation system

Li¹,

Li²,

Liang³

2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

Enhancing the reliability of shipborne INS/GNSS integrated navigation system during abnormal sampling periods using Bi-LSTM and robust CKF

Zhang,

Li,

Liu

et al. 2023

Ocean Engineering

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An Adaptive Integrated Positioning Method for Urban Vehicles Based on Multitask Heterogeneous Deep Learning During GNSS Outages

Cheng,

Gao,

2023

IEEE Sensors J.

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GNSS/MIMU tightly coupled integrated with improved multi-state ZUPT/DZUPT constraints for a Land vehicle in GNSS-denied enviroments

Cited by 4 publications

References 19 publications

A zero-velocity update method based on neural network and Kalman filter for vehicle-mounted inertial navigation system

A zero-velocity update method based on neural network and Kalman filter for vehicle-mounted inertial navigation system

Enhancing the reliability of shipborne INS/GNSS integrated navigation system during abnormal sampling periods using Bi-LSTM and robust CKF

An Adaptive Integrated Positioning Method for Urban Vehicles Based on Multitask Heterogeneous Deep Learning During GNSS Outages

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