The last edition of the European Space Week, held in Helsinki, the E-GNSS User assembly contained, among others, a series of keynote talks that presented the status of the user needs and requirements in terms of geolocation in different market segments such as consumer solutions, IoT, aviation, road, ...

Rokubun presented the status for the market segment of consumer solutions and IoT. In order to tackle this task, we issued a small survey to know the status on some of the most relevant Key Performance Indicators for GNSS (e.g. accuracy, Time-To-First-Fix, availability, integrity, ...). These KPI are listed in the last GSA Market Report (see page 9). This post includes below the results of the survey, whose main conclusions are:

  • In terms of accuracy, 50cm to 1m of error seem to be the dominant need. This requirement can be easily met with dedicated GNSS chipsets in IoT and feasible in smartphones with dual-frequency capabilities when differential techniques such as RTK are applied. Higher accuracy requirement (less than 50cm) is still of relevance but this is still a challenge in LBS with the current hardware (in particular with the antenna limitations).
  • With the increased popularity of, among others, augmented reality, knowing the orientation of the device is gaining relevance. Fortunately enough, the sensors available in smartphones (GNSS and Inertial Measurement Unit) are enough to satisfy this requirement.
  • Regarding continuity of position solutions, 1second rate seem to fulfill most of the user needs. Smartphones already satisfy this requirement while GNSS chipsets in IoT devices can go to rates as high as 10Hz. For applications related to IoT, lower rates are also acceptable, which helps in keeping longer battery life.
  • Robustness against jamming and spoofing is also gaining relevance in this market segment, in part due to the drop of the price tag for the RF components needed to build spoofers.
  • Finally, a new requirement that might be included in upcoming User Consultation Platforms correspond to data usage. The survey evidenced that, while in some cases data consumption is not relevant, there are some other cases such as IoT where the bandwidth is scarce, which limits the applicability of techniques that require differential corrections such as RTK, that give access to accuracies in the centimetric ballpark. There seems to be then a trade-off between achievable accuracy and data consumption limitation.

What do you think? Does these results match the needs on your specific application? Let us know your opinion and remember you can still contribute to the survey if you want.