GNSS navigation requires an unobstructed line-of-sight view of four or more satellites with suitable geometry to compute latitude, longitude, altitude, and time. GNSS signal weakens in degraded environments such as Ur...
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ISBN:
(纸本)9781665482370
GNSS navigation requires an unobstructed line-of-sight view of four or more satellites with suitable geometry to compute latitude, longitude, altitude, and time. GNSS signal weakens in degraded environments such as Urban Canyons, Tunnels, Under Passes, and Green Tunnels. Therefore, GNSS alone cannot provide reliable navigation support in challenging environments. To address this limitation, GNSS can be augmented with multiple other navigation sensors to provide an integrated solution, including inertial measurement units, magnetometers, and radars. Low-cost, small size and lightweight MEMS sensors are used for a wide range of navigation applications. However, adding each sensor increases the complexity of the systems as each sensor independently measures a particular parameter. Multi-sensor data fusion techniques, such as Kalman Filter (KF), play a vital role in improving the navigation accuracy of the system. This paper reviews multiple sensor schemes for integrating two accelerometers, a gyroscope, a magnetometer, and Adaptive Cruise Control Radar augmented with GNSS to provide an integrated multi-sensor navigation system. These multiple sensor schemes were tested in an actual road trajectory in Kingston. In addition, GNSS outages were intentionally introduced on this road trajectory to examine the performance of different schemes for various motion dynamics.
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