United Kingdom

Navigation 2021

Multi Sensor Fusion for Autonomous Space PNT

### Welcome to Navigation 2021!

Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

Navigation and timing are critical to the world we all inhabit. We believe that the work of the wider navigation community enables societal benefit including support to national grand challenges and also the United Nations’ Sustainable Development Goals. To achieve this requires collaboration and understanding across science, technology and practice.

Navigation 2021 is about much more than technology innovation, it also showcases science and research from across the wider community, including animal navigation, cognition and human factors.


Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

technical paper

Navigating the new normal: How Google maps changed as a result of the COVID-19 pandemic

Session 3.5.

Position integrity for cooperative land vehicle networks

Development of GNSS Augmentation Integrity Messaging Standards for Automotive Applications

High-Integrity Measurement Error Time Correlation Modeling Using PSD-Bounding of Experimental Data

Session 3.6.

Maritime Receiver SBAS L1 Standardisation – IEC process

A New Space Approach to Commercial LEO PNT

The ontogeny of cognitive maps in the real world

The poster will present a new approach to teaching location estimation techniques, including GNSS. The new approach assumes relatively little (undergraduate-level familiarity with linear algebra, calculus, and a bit of continuous probability) and is therefore accessible to undergraduate students in math, computer science, physics, and engineering. Most existing approaches assume a lot more (e.g., extensive background in statistical signal processing) and are therefore accessible to much narrower groups of students. The material, along with problems (many solved) and small programming exercises, is available as a book (Location Estimation from the Ground Up, Sivan Toledo, SIAM 2020). 

The material covers a wide range of techniques and ideas, starting from linear least squares, probabilistic justifications for least-squares (maximum likelihood), non-linear least squares, time-of-arrival location estimation and GNSS, signal processing for arrival-time estimation (code phases in GNSS), Kalman filtering, and integer least squares (carrier-phase GNSS observations and RTK). The material also covers important topics like error analysis (Cramer-Rao bounds, estimation of error covariance matrices, and DOP).

The presentation is consistent and thorough. Most algorithms are fully explained, in the sense that they can be implemented by the students (QR factorization, FFT, Kalman filtering, and algorithms for integer least squares). A few algorithms are explained at a higher level, to allow students to understand their behavior but without low-level details (nonlinear optimization and the SVD).

The poster will present the approach and will encourage discussion of how courses in this area are structured and how to widen their target audience.

Location Estimation from the Ground Up: A New Teaching Approach

keynote

live session recording

lightning talk

https://d3smihljt9218e.cloudfront.net/transcript/30303/subtitle/ee24c6975e362464380a243a387a0b76.vtt

English (automatic)

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Multi Sensor Fusion for Autonomous Space PNT

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