The objective of this dissertation is to compare the mean squared error (MSE) of the estimated path of a pedestrian using one or two inertial measurement units (IMUs) in the absence of GPS signals. Path estimation using the fusion of measurements from one inertial measurement unit (IMU) is achieved with three orthogonal accelerometers, three orthogonal gyroscopes, and three orthogonal magnetometers. Step length estimation employs the vertical acceleration measurements of the hip to evaluate the horizontal displacement from the inverted pendulum model of walking with the leg being the pendulum’s arm and integrating the vertical acceleration twice to find the vertical displacement. The periodic nature of the vertical acceleration of the hips is utilized to decrease the error from the integrations by integrating an analytical approximation for each half step. The accelerometers’ measurements are used to correct the orientation when the only measured acceleration is the gravity field vector. Meanwhile, the orientation is updated from the gyroscopes’ measurements when the person is accelerating. When the orientation is corrected the heading angle is evaluated from knowing the previous angle and the change in the heading angle from the gyroscopes’ measurements where the initial heading angle is known. The heading angle is also found from the magnetometers’ measurements when the gyroscope and the magnetometer change at the same rate. Quaternion rotation operation is used to evaluate the orientation updates of the pedestrian to decrease the computational complexity. The accelerometers’ measurements and the gyroscopes’ measurements are pre-filtered using Kalman filters (KFs) designed from the knowledge of the noise terms present in their static measurements using Allan variance (AV). The fusion of two IMUs for path estimation is found by averaging estimations from the individual IMUs. From the experiments the MSE in path estimation for the IMU with worse estimation is reduced by an average of 23.00 % and up to 50.80 %.
|Advisor:||Daigle, John N.|
|Commitee:||Viswanathan, Ramanarayanan, Waddell, Dwight, Wang, Feng|
|School:||The University of Mississippi|
|School Location:||United States -- Mississippi|
|Source:||DAI-B 82/8(E), Dissertation Abstracts International|
|Subjects:||Electrical engineering, Mechanics, Electromagnetics, Applied Mathematics|
|Keywords:||Allan variance, Inertial measurement unit, Kalman filters, Mean squared error, MPU-9250, Path estimation|
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