Modern smartphones have all the sensing capabilities required for accurate and robust navigation and tracking. In specific environments some data streams may be absent, less reliable, or flat out wrong. In particular, the GNSS signal can become flawed or silent inside buildings or in streets with tall buildings. In this application paper, we aim to advance the current state-of-the-art in motion estimation using inertial measurements in combination with partial GNSS data on standard smartphones. We show how iterative estimation methods help refine the positioning path estimates in retrospective use cases that can cover both fixed-interval and fixed-lag scenarios. We compare estimation results provided by global iterated Kalman filtering methods to those of a visual-inertial tracking scheme (Apple ARKit). The practical applicability is demonstrated on real-world use cases on empirical data acquired from both smartphones and tablet devices.
The classical inertial navigation literature is extensive (see the books @cite_3 @cite_27 @cite_18 @cite_15 , for example) but is mainly focused on navigation of large vehicles with relatively high quality inertial sensors. Even though the theory is solid and general, practice has shown that a lot of hand-tailoring of methods is needed to actually get working systems. Since we focus on navigation approaches using consumer-grade sensors in small mobile devices, the literature survey below concentrates on recent work in that area.
@cite_27 @cite_18 @cite_3 @cite_15
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From the Publisher: "Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics." "The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems." "Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area."--BOOK JACKET. Inertial navigation is widely used for the guidance of aircraft, missiles ships and land vehicles, as well as in a number of novel applications such as surveying underground pipelines in drilling operations. This book discusses the physical principles of inertial navigation, the associated growth of errors and their compensation. It draws current technological developments, provides an indication of potential future trends and covers a broad range of applications. New chapters on MEMS (microelectromechanical systems) technology and inertial system applications are included. Coordinate frames and transformations ordinary differential equations inertial measurement unit inertial navigation system system error dynamics stochastic processes and error models linear estimation INS initialization and alignment the global positioning system (GPS) geodetic application. This book offers a guide for avionics system engineers who want to compare the performance of the various types of inertial navigation systems. The author emphasizes systems used on or near the surface of the planet, but says the principles can be applied to craft in space or underwater with a little tinkering. Part of the material is adapted from the authors doctoral dissertation, but much is from his lecture notes for a one-semester graduate course in inertial navigation systems for students who were already adept in classical mechanics, kinematics, inertial instrument theory, and inertial platform mechanization. This book was first published in 1971 but no revision has been necessary so far because the earth's spin is being so much more stable than its magnetic field.