Enhancing Land Vehicle Navigation in Challenging Environments Using Consumer Level Devices
Creators: name: Moussa, Mohamed
Publisher: name: Graduate Studies
Year: 2020
Subjects: subject: Land Vehicle Navigation
subject: INS
subject: Inertial Aiding Navigation
subject: Low-cost sensors
subject: EKF
subject: Mass Flow sensors
subject: Engineering--General

description: Recently there has been a massive effort in developing navigation systems for the self-driving cars. GNSS/INS integration is the most common sensor fusion technique to estimate the land vehicles navigation states. However, this system is not perfect in all operating situations as GNSS signals may suffer from signal outages, and/or multipath in urban and foliage areas. In such cases, INS provides the navigation solution which is degraded after a very short period due to the large drifts of the INS. During GNSS signal outage, INS should be assisted with other aiding sensors to mitigate its large drift. These sensors may include magnetometers, odometers, cameras, Light Detection And Ranging (LIDAR), Radio Detection And Ranging (RADAR), etc. Maps aiding navigation is used in many previous researches to help low-cost INS in GNSS denied environments. Consumer Portable Devices (CPDs) are widely used all over the globe. CPDs contain many sensors that could particpate in the enhancement of the land vehicles. Unfortunately, there are some limitations associated with the previous mentioned aiding techniques related to their high price, high computation and processing cost, weather and surrounding environmental effects in addition to the map aiding method drawback that is based on the avialability and the update rate of the required maps. Therefore, autonomous land vehicles navigation using low-cost sensors integrated systems has attained a lot of research interest The main objective of this research is to develop various land vehicle navigation systems that work in GNSS challenging environment, based on low-cost, non conventional sensors, and CPDs to add a redundant land vehicle motion information, reduce the cost of the navigation systems and thus decrease the overall self-driving car cost and provide an accepatble navigation performance. Two low-cost non-conventional wheel odometry systems are proposed where the first system is based on multiple ultrasonic sensors while the other is developed using multiple low-cost gyroscopes. These systems are implemnted to aid the low-cost INS in GNSS signal outage to reduce its drift. The relative alignment between the CPD and vehicle frames is very vital process when using CPD in the land vehicle navigation. However, it requires other sensors to estimate the relation between the CPD and vehicle coordinaite systems and it should be in motion. A new static relative alignment method is developed based on the vehicle vibration signature pattern which does not require any additional sensors. Moreover, a steering wheel angle estimation method is developed using CPD self-contained accelerometers that is attached to the steering wheel where this information is used in aiding the low-cost INS in GNSS challenging environment. Furthermore, different DR and aiding systems are investegated based on the land vehicle information and the CPD sensors to assess the navigation performance for such systems. Moreover, multiple CPD navigation systems are investegated using federated fusion technique.Two non-conventional navigation systems are proposed where the first depends on the ECU sensors to provide a redundant land vehicle speed information to aid the low-cost INS in GNSS signal outage. The second system is based on mass flow sensors that benefits from the aerodynamics of the vehicle motion to provide the speed and the heading information in indoor environment.The performance of the proposed low-cost navigation techniques show promising navigational results and low complexity efforts.