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Want reliable coronavirus tracking? Accurate, resilient geo-time stamping is key

Several nations are already using time and location data from smartphones to help track the coronavirus. They’re using apps that query a user’s health status and allow the collection of data showing when and where unhealthy people had traveled, helping map the virus’ spread. The apps rely on GPS (or more generically, GNSS – Global Navigation Satellite System, of which GPS is one of four international constellations) for an accurate position and time stamp.

Can this geo-time stamp be trusted?  Probably yes, in this simple example, but perhaps not for more-complex use cases. As the combination of worldwide mobility information and big data analytics enables the creation of actionable intelligence for decision-making, we must ensure time and location data is resilient and impossible to undermine, especially in cases that involve human safety. Therefore, three factors must be considered:

1. Accuracy. For a simple virus tracking app, position to the nearest 10s or 100s of meters is sufficient. However, for other applications, one meter or even centimeter-level accuracy may be necessary -- much more than a smartphone delivers. Specialized GNSS equipment and other devices can provide higher position resolution and accuracy.

Most data center networks use the Network Time Protocol for data management, which can give 1-100 millisecond accuracy in most cases, but sometimes this is not enough. Time synchronization derived from GNSS can yield 1-10 nanosecond accuracy, though distributing that precise time to the source can be challenging.

Another common source of inaccuracy comes from data that is geo-time-stamped at the point of processing, rather than at the point of sampling. For example, consider the connected-car use case: Real-time monitoring of all the cars in a city shows when and where they slow down, which can support inferences of  traffic jam locations, slippery road conditions, etc.  But if the time tagging is done at the processing center and not at the car, then network delays will make the measurement much less accurate and could lead to false conclusions.  In addition, if the car is time-stamping the data and its clock is not synchronized with global time, that time stamp will be wrong.

2. Integrity. Even though cybersecurity is critical for any time and location application, GNSS signals can be easily jammed or spoofed, which could lead to disastrous consequences. Likewise, it’s also critical to know if and when the integrity of the Positioning, Navigation and Timing (PNT) data -- has been compromised. There are new, emerging techniques to detect and protect against such events in GNSS systems.

3. Resiliency. Reliable, fault-tolerant and secure systems are considered resilient. In February, the administration issued an executive order requiring resiliency in all PNT systems used in critical infrastructure. This includes telecommunications networks, financial and banking systems, the power grid, transportation systems and others. All of these critical infrastructure systems require accurate and reliable PNT information. To achieve the resiliency required, we see two main approaches:

  • Toughen GNSS: Smart antennas, advanced receivers with multi-frequency and multi-constellation capability and advanced digital signal processing techniques can filter and reject jamming and spoofing.
  • Augment PNT with other sources. PNT signals from low Earth orbit satellites are emerging as a new source for precision time that are 1,000 times stronger than GNSS These satellite time and location services are encrypted, making them much harder to jam and resistant to spoofing. Advanced Precision Time Protocol timing can also be delivered over fiber -- a technology dubbed “White Rabbit” -- to provide nanosecond level timing across the network. In addition, emerging Network Time Security protocols will ensure the integrity of this timing.

Distributed big data processing and mobility are driving the need for accurate, resilient PNT data. GNSS is a wonderfully accurate and ubiquitous way of geo-time stamping data, but it is not resilient enough for use in critical operations. Fortunately, there are alternatives to toughen and augment GNSS to make it resilient.

About the Author

John Fischer is the VP of advanced R&D at Orolia.


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