Dual-Antenna GNSS Integrated With MEMS for Reliable and Continuous Attitude Determination in Challenged Environments

Abstract

Attitude determination based on global navigation satellite systems (GNSS) is characterized by high-precision, low-cost, and no error accumulation. However, GNSS harsh-signal environments will degrade the accuracy and reliability of GNSS attitude. In this case, micro-electro-mechanical system (MEMS) inertial sensors are often integrated with dual-antenna GNSS for more reliable and continuous attitude determination. In this paper, we fused dual-antenna GNSS and MEMS to acquire heading, pitch, and roll with high accuracy in GNSS challenged environments. Instead of a Euler angle representation, the misalignment is used to build the state model in the integrated Kalman filter. Attitudes derived from dual-antenna GNSS and smoothed acceleration are adopted as measurements. It can be found that this filtering architecture is actually a subset of loosely coupled GNSS/MEMS integration. Therefore, the proposed module can be easily embedded into loosely coupled integration. In addition, due to the disadvantage that GNSS is sensitive to signal interference and obstacles, the fault detection and exclusion strategy was proposed to avoid the filtering divergence and to improve the reliability of attitude determination. Finally, two vehicular tests with a 1.12-m baseline conducted in GNSS friendly and challenged environments showed that the proposed attitude determination algorithm could detect and exclude all GNSS-attitude outliers, thus achieve the high accuracy of 0.2°, 0.39°, and 0.28° for heading, pitch, and roll angles in the challenged environment, respectively. With the MEMS-gyroscope aiding, the attitude gaps caused by GNSS outages are bridged. For a 300-s outage duration, the average accumulated attitudes errors are 2.37°, 0.88°, and 1.40°.