Assessment for INS/GNSS/Odometer/Barometer Integration in Loosely-Coupled and Tightly-Coupled Scheme in a GNSS-Degraded Environment

Kai Wei Chiang, Hsiu Wen Chang, Yu Hua Li, Guang Je Tsai, Chung Lin Tseng, Yu Chi Tien, Pei Ching Hsu

Research output: Contribution to journalArticlepeer-review

51 Citations (Scopus)

Abstract

With the increasing demands for seamless landvehicle navigation, systems with robust performance are required in highly urbanized areas. The traditional INS/GNSS integration is widely applied to solve this issue. However, the system still suffers from bad GNSS signal reception and INS time accumulated errors that seamlessness and stability are difficult to maintain. In this study, the performance of the low cost INS/GNSS with aiding sensors, such as an odometer and barometer, was evaluated for both the loosely-coupled (LC) scheme and tightly-coupled (TC) scheme. Moreover, considering barometric error accumulation, a vehicle-behavior based drift control method has been proposed. An experiment was conducted under harsh GNSS-degraded scenarios to assess the characteristics and performance for different sensor combinations, using single constellation (GPS) with single-frequency (L1 band) measurement. Overall, the TC scheme without additional strategies in detecting abnormal measurement encounters more challenges to achieve stable performance. In an INS/GNSS/barometer system with the proposed drift control method, error accumulation under unpredictable environmental changes was successfully mitigated in both schemes. The proposed method can maintain a height accuracy of 2-meter level root mean square even after a long term operation. In an INS/GNSS/odometer combination, improvements were observed in the horizontal and vertical direction for both schemes. According to statistical analysis, an INS/GNSS/odometer/barometercombination shows 16.57% and 6.11% in the horizontal, and 30.71% and 71.28% in the vertical for the LC scheme and TC scheme, compared with an INS/GNSS combination.

Original languageEnglish
Article number8907859
Pages (from-to)3057-3069
Number of pages13
JournalIEEE Sensors Journal
Volume20
Issue number6
DOIs
Publication statusPublished - 2020 Mar 15

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

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