Ionospheric Trough Measurements of the Earth’s Core and Distances to Satellites: Comparison with Madrigal 23,24
Researchers are working on using other smartphone sensors in other ways. The 2020 showed how people can sense earthquakes with their phones, and warn others who have yet to be hit. It is possible for Apple users to view an app that uses similar technology.
Global Positioning System (GPS) and other GNSS receivers estimate distances to satellites by measuring the time for a radio signal to travel from a satellite to a receiver. Significant errors in the calculations of the distance to satellites are caused by the effect of Ionospheric TEC. This is a large source of gps error, and many devices use a coarse model of the ionospheric TEC to compensate. Most phones use an 8-parameter model, mitigating about 50% of the ionospheric error7. This model was created in the beginning of theGPS and was designed for the limited computation and bandwidth at the time.
The TEC maps from phone measurements capture the day–night cycle, with the peak in ionization in the early afternoon, and also show the Ionosphere Equatorial Anomaly, a crest of ionization north and south of the geomagnetic equator with a characteristic dip southwards over South America (Supplementary Videos 1 and 3).
Storm-enhanced density over North America was also seen in another geomagnetic storm on 5 November 2023. This time, phone measurements also reveal a depletion in ionization over Europe, a so-called mid-latitude ionospheric trough. Extended Data Fig. Maps from 180,000 phones are compared by 3. During the storm, there is a striking difference between the phone data and the previous day’s data.
We evaluate our phone-based VTEC maps by comparing with the Madrigal database23,24. This database combines line-of-sight STEC measurements from over 9,000 monitoring stations for the US GPS and Russian GLONASS constellations at 30-second intervals, with carrier-phase smoothing to reduce noise. Our VTEC maps are spatially discretized into approximately 98,000 cells and temporally discretized into 1-minute windows. We compare our VTEC estimates in each cell-minute with measurements from the Madrigal database over the period of 10 September to 6 November 2023 to assess the accuracy and coverage of our measurements.
We solve for VTECtrue and DCBphone with weighted least squares over 10 minutes. Over 100,000,000,000 phones and up to 30,000 S2 cells are present in a typical time window. This is tractable by exploiting the sparsity and block structure of the system. Our solutions show that DCBphone clusters by phone model (Extended Data Fig. 1).
Although DCB values for satellites are published22, we must calculate the DCB for each individual phone. We get a linear equation for the line-of-sight measurement when we use STEC, VTEC and rearranging.
The differential code bias is caused by the latencies in the hardware in satellites and mobile phones. The biases shift the measured STEC from its true value as follows:
A GNSS receiver measures the ionosphere TEC along a line of sight from a satellite using the difference in measured travel times18, t1 and t2, for the satellite signal on two different frequencies, f1 and f2, respectively. The first order of the frequencies is approximated by the TEC along the path.
where c is the speed of light and re is the classical electron radius. TEC values can be up to 200 TECU. The noise of the phone data has a standard deviation of 70 TECU and is 30 times larger than the noise for traditional monitoring stations. Carrier-phase smoothing19 would ordinarily reduce the noise further (to 0.2 TECU (ref. 20)) but carrier-phase measurements are often unreliable on phones. Figure 2 compares the TEC measured by a particular monitoring station with the measurements from 1,011 nearby phones. They agree with the station measurements when averaged despite the larger noise in individual phones.
Scientists used to think of phones as end users of navigation services. Flipping this on its head to use phone measurements as input data is “new territory”, he says. “This paper marks an exciting shift.”
Google maps Earth’s ionosphere and improve GPS: An analysis of a new NASA experiment with the Madrigal Database in South America
Coster, who works on the Madrigal Database, says that for science to really benefit, they need to be able to access data from thousands of ground stations. A spokesperson for Google told Nature’s news team that the data behind the study will be released alongside the paper, but there are currently no plans to provide fresh data in real time.
Williams says that efforts are already under way to use this technique to improve location accuracy for Android users. The data should be used for studies of the Earth’s upper atmosphere. The map shows bubbles in ionized gas over South America that hadn’t previously been seen.
Anyone with an Android phone — and who allows Google to collect sensor data to improve location accuracy — was eligible to contribute to the study. The data was aggregated, so that individual devices are not identifiable, says the firm.
The Google team succeeded in part thanks to the volume of data obtained. The noise averages out and you still get a clear signal when combined in large numbers. There are monitoring stations for phones in every city.
When charged particles from the Sun can boost electron density, the world would be a lot smaller if the corrections were not there. The use of ground-based receiver stations to make these maps are rare in many parts of the world.
Radio signals travelling to Earth are slowed down when the air is partly ionized. This can affect the nanosecond-precision timing that satellite navigation devices use to pinpoint their locations, with potentially serious impacts on aeroplane landings and autonomous vehicles.
Source: Google uses millions of phones to map Earth’s ionosphere and improve GPS
Anthea Coster: Physics at the Massachusetts Institute of Technology (MIT), New York, March 1905 – April 11, 2015 – Summary and Update
An thea Coster is a physicist at the Massachusetts Institute of Technology in Cambridge. It fills in the map in areas where we need more information.