A Long Look at Advanced Multisensor Navigation and Positioning

A modern-day fable related by Steven Covey tells of a civil engineer leading a crew engaged in building a road through a dense jungle. Each day the engineer’s adept management, the crew’s motivation and energy, and the high-tech equipment at their disposal pushed the new road well beyond scheduled targets. Midway through the allotted month, the engineer decided to climb to the top of a tree to see if he could get a distant glimpse of the destination. After a few minutes, he called down to his crew, “Wrong jungle!”

This comes to mind as we consider the well-known fact that the next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments, to meet the needs of a variety of mission-critical applications. It’s no secret that not a single navigation technology, among scores available to us, is robust enough to meet these requirements by itself. A multisensor solution is required.

Although many new navigation and positioning methods have been developed in recent years, little has been done with all-encompassing vision to bring them together into a robust, reliable, and cost-effective integrated system. Almost all the solutions proposed — and I have conveyed many of them in the pages of GPS World, thanks to the expert engineers who designed and tested them — spring from the requirements of a particular situation, application, or industry sector. Their parameters are suitably specialized.

What’s been lacking so far is an over-architecture for the entire field. Paul Groves of University College London has outlined such a structure in an article that will appear in the September issue of the magazine: “Four Key Challenges to Multisensor PNT.” This material was first presented at the IEEE/ION Position Location and Navigation Symposium (PLANS) in Monterey, California in May of this year.

The magazine article will describe each challenge in turn. In each case, Groves explains the problem, proposes one or more solutions, and identifies the issues that must be resolved in order to implement those solutions. He also presents the results of some preliminary context-detection experiments and illustrates some of the problems using results from several UCL research projects. The discussion is illustrated with results from research into urban GNSS positioning, GNSS shadow matching, environmental feature matching, and context detection

The four challenges: complexity, context, ambiguity, and environmental data handling.

• Complexity – How to find the necessary expertise to integrate a diverse range of technologies, how to combine technologies from different organizations that wish to protect their intellectual property, how to incorporate new technologies and methods without having to redesign the whole system and how to share development effort over a range of different applications.
• Context – How to ensure that the navigation system configuration is optimized for the operating environment and host vehicle (or pedestrian) behavior when both are subject to change.
• Ambiguity – How to handle multiple hypotheses, including measurements of non-unique environmental features, pattern-matching fixes where the measurements match the database at multiple locations, and uncertain signal properties, such as whether reception is direct or non-line-of-sight (NLOS).
• Environmental Data Handling – How to gather, distribute, and store the information needed to identify signals and environmental features and define their points of origin or spatial variation.

As Groves relates in his article, many new positioning techniques have been investigated over the past fifteen years.

• Wi-Fi positioning
• Ultra-wideband (UWB) positioning
• Positioning using phone signals
• Positioning using television signals and other signals of opportunity (SOOP)
• Bluetooth low energy positioning
• Laser-based position fixing and dead
• Pedestrian dead reckoning (PDR) using step detection
• Pedestrian map matching Error! Reference source not found.
• Magnetic anomaly matching
• Activity-based map matching
• GNSS shadow matching

There have also been improvements to existing technologies.

• Hardware required for visual navigation
• Micro-electro-mechanical systems (MEMS) technology
• Cold-atom technology and nuclear magnetic resonance (NMR) gyros offering aviation-grade performance with compact sensors
• Legacy radio navigation systems, such as Distance Measuring Equipment (DME) and Loran (in Europe and South Korea) are being modernized
• Doppler positioning is being reintroduced using Iridium communication satellites

Finally, GNSS itself has been enhanced through multiple constellations in a continual state of upgrade and renewal, high-sensitivity receivers and network assistance, and augmentation by commercial pseudolite systems.

Maybe it’s time for a high-level perspective on all these adjoining jungles, if we want to find our way out of them.

Potential components of a car navigation system using commonly available equipment and other low-cost sensors.