Low-Cost Integrated Navigation Systems Using Nonlinear Observer Theory

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The main motivation for the proposal is summarized below: - Develop low-cost integrated navigation using MEMS components with lower computational footprint than the Kalman filter and develop explicit stability guarantees for the nonlinear observers. - De monstrate how nonlinear observers can be implemented on light-weight embedded computers with limited processing capacity. - Nonlinear observer theory, MEMS technology and embedded systems are changing the rules of the game and opens for the development of low-cost compact position, velocity and attitude (PVA) estimation. The project will focus on methods which can be used in as low-cost consumer electronics, cars, navigation systems for autonomous underwater vehicles (AUVs), ships, unmanned aerial vehicle s (UAVs) etc. - Demonstrate that it is possible to develop effective computer algorithms that can be implementation using only a fraction of the source code when compared to a standard EKF implementation. This will simplify implementation, maintenance and software documentation. - Compare and verify the the performance to commercial EKF-based systems in cooperation with Maritime Robotics and FFI. - The project targets education of three PhD and eight MSc candidates (Working Packages 1-3) dealing with: WP1: Integrated observer design with a North-seeking strapdown MEMS-based gyrocompass WP2: Nonlinear tightly integrated filters for attitude, velocity and position WP3: Model-based nonlinear integration filters for INS and position measurements - T he results will be published at conferences and in the top ranked journals in the field.