An Accurate Land-Vehicle MEMS IMU/GPS Navigation System Using 3D Auxiliary Velocity Updates

Abstract

In the last decade, the Land-Vehicle Navigation (LVN) market has grown rapidly. For most LVN systems, GPS is used for positioning. However, GPS has poor accuracy in urban areas due to signal blockages. Therefore, the LVN market has targeted the integration of other sensors with GPS. In this case, sensors' cost and size are major issues. Recent advances in MEMS inertial sensors made it possible to develop low-cost and compact IMUs. However, MEMS provide poor accuracy when used without updates (e.g., during GPS outages). In such periods, other updates are required for better performance. Vehicle full-stops, i.e., Zero-Velocity-Updates (ZUPTs), are usually applied for this purpose. However, this is not practical especially when GPS blockages are frequent. In this paper, 3D Auxiliary Velocity Updates (AVUs) are used, namely, non-holonomic constraints and odometer-derived velocity. Using kinematic MEMS/GPS data with several GPS signal blockages, the results showed a significant accuracy improvement after applying AVUs.

The four key challenges of advanced multisensor navigation and positioning

“…For example, cars normally remain on the road, effectively removing one dimension from the position solution. Their wheels also impose constraints on the way they can move, reducing the number of inertial sensors required to measure their motion [83] [84]. Similarly, PDR using step detection depends inherently on the characteristics of human walking [23] [24].…”

Ultra-tightly Coupled GPS/Vehicle Sensor Integration for Land Vehicle Navigation

“…In order to limit the errors induced by the reduced IMU/GPS integrated system, the wheel speed sensor and non-holonomic constraints are applied in this work. The three-dimensional (3D) The non-holonomic constraints are derived assuming the vehicle does not slip in the across track direction, which is a reasonable assumption for travel in a constant direction in the absence of ice or snow [16,18,23]. Since the two assumptions are valid under most normal driving conditions, the additional description of the vehicle dynamics provided by the constraints improves navigation performance.…”

“…A wheel speed sensor which is another standard sensor in most vehicles can be used to further improve navigation accuracy and system redundancy [16]. To integrate a wheel speed sensor with a GPS/INS system, centralized and decentralized approaches have been studied by many researchers [16][17][18]. Since the wheel speed sensor only measures velocity in the vehicle's longitudinal direction, non-holonomic constraints and wheel speed sensorderived velocity can form three-dimensional auxiliary velocity updates for the Kalman filter.…”

“…Since the wheel speed sensor only measures velocity in the vehicle's longitudinal direction, non-holonomic constraints and wheel speed sensorderived velocity can form three-dimensional auxiliary velocity updates for the Kalman filter. Improvement of position and attitude accuracy has been obtained when using such updates in MEMSbased integrated system [18].…”

GPS/Reduced IMU with a Local Terrain Predictor in Land Vehicle Navigation

“…To this end, land vehicle navigation (LVN) plays a critical role and this is evident from the large number of publications on the topic in recent years. Specifically, LVN studies have focused on low-cost microelectro-mechanical system (MEMS) inertial measurement units (IMUs) [1][2][3][4], reduced IMUs [5][6][7][8][9][10][11], and on GPS and inertial navigation system (INS) integration [4,12] to GPS/IMU plus more vehicle sensors integration [2,3].…”