GNSS/MIMU tightly coupled integrated with improved multi-state ZUPT/DZUPT constraints for a Land vehicle in GNSS-denied enviroments. (3rd July 2021)

• Record Type: Journal Article
• Authors: Ning, Yipeng; Sang, Wengang; Yao, Guobiao; Bi, Jingxue; Wang, Shida
• Is Part Of: International journal of image and data fusion. Volume 12:Number 3(2021)
• Page Start: 226
• Page End: 241
• Publication Date: 2021-07-03
• Subjects: GNSS/INS -- tightly-coupled -- zero-velocity detection -- Vondrak filter -- GNSS outage; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2020.1829718
• Languages: English
• ISSNs: 1947-9832

Abstract

ABSTRACT: A GNSS/INS integrated navigation system has been intensively developed and widely applied in multiple areas. It can provide high accuracy position, velocity and attitude for vehicle with appropriate data fusion algorithm. However, the overall performance of a low-cost GNSS/MEMS IMU frequently degrades in shaded environment. The traditional constraints GNSS/MIMU algorithm based on zero-velocity detection can effectively increase positioning performance, but easily be susceptible to false detection. This article aims to improve a ZUPT/DZUPT constraints model to improve the accuracy of navigation solutions during satellites signal blockages for different motion states. Firstly, we present a tightly coupled strategy to integrate GPS/BDS and INS by applying EKF. Then, a compositive static zero-velocity detection scheme is carried out by using the Vondrak low pass filter, GNSS/INS calculated velocity and the original data of INS. Meanwhile, a dynamic ZUPT constraint model is also constructed based on the motion characteristics of vehicle. An vehicle test was performed to validate the new algorithm. The results indicate that proposed method can effectively improve the success rate of zero-velocity detection. When the satellite signal is interrupted for 120 s, the position and velocity accuracy of the vehicle are improved by 74.7%~ 96% and 47%~ 86.2% respectively.