Design, Implementation and Key Issues of Adaptive Tightly Coupled MEMS INS/GPS Integration System

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Tightly-coupled integrated system is advantageous in providing seamless navigation solution compared with other integration schemes, and is attractive in multiple application fields. This thesis focuses on the design, implementation of adaptive tightly-coupled integrated navigation system with the aiding of external measurement. The key issues investigated and problems solved in this dissertation are: 1. It presents four novel adaptive noise estimation approaches. These methods rely on the observation information to estimate the measurement noise property and error characteristic. The noise assessment method makes use of difference operation to eliminate the effect of other elements and this process is decoupled from the filter calculation loop. Thus, the covariance matrix estimation result will not be coupled with the state vector error, and this existed problem in traditional adaptive Kalman filter is avoided. 2. It proposes a new low-cost MEMS sensor in-filed calibration algorithm. The navigation mission requires calibration before started. The proposed approach can perform calibration of the sensors without any requirement or special needs. The calibration scheme is convenient to be accomplished by simple hand rotation in space. The bias, scale factor error and non-orthogonal error are able to be identified. 3. It investigates the Euler angle based attitude estimation. The Euler angle attitude update is constrained for further practical application owning to its singularity problem. The singularity problem will cause the attitude procedure discontinue and involves more estimation error. An intelligent coordinate switch algorithm is proposed to overcome this drawback and has achieved a good performance. The adaptive noise estimation approach is also applied in the filter to adjust the weight of observation model, which prevents the negative effect of external acceleration. 4. It introduces the adaptive noise estimation theorem and external observation in the standard tightly-coupled integrated system, and establishes the system hardware platform to test the validation. The height and heading information measured by barometer and magnetometer are used involved in measurement model to provide aiding information. A switch filter strategy is designed to save computational time, and the adaptive noise estimation approach is used to acquire the GPS measurement error characteristic. Both simulation and practical tests are conducted to verify the system.
Zhou, Q. (2017). Design, Implementation and Key Issues of Adaptive Tightly Coupled MEMS INS/GPS Integration System (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from doi:10.11575/PRISM/25580