Fii (Forecast Ionosphere Irregularities) is an innovative product to forecast ionosphere irregularities.
Our invention concerns a method for forecasting ionosphere total electron content and/or scintillation parameters.
We developed a method of TEC (Total Electron Content) and scintillation empirical forecasting, in particular short-term forecasting (seconds to minutes). The output of the method is necessary to feed mitigation algorithms aiming at improving accuracy on GNSS precise positioning techniques (RTK, NRTK, and PPP) under ionospheric harsh conditions.
Fields of applications of GNSS precise positioning techniques
Precision agriculture (PA)
Although the concept of PA was introduced at the beginning of the last century, the technology available so far was not able to put it in practice. With the goal of increasing the field management yield, for almost two decades the concept of PA has evolved and is now treated as an agricultural practice which uses technology information based on the principle of variability of soil and climate. Based on specific geo-referenced data, it deploys the process of agricultural automation, dosing fertilizers and pesticides differently. The technological elements that highly contributed to the development of this concept were microprocessor and GNSS, which are coupled and integrated on the harvesters, seeders and other implements, allowing the data collection, cumulative tabulation and dosed application with localized inputs.
Within this context, one of the fastest growing segments is the localized application of pesticides, and fertilizers as well as the autopilot that enables work for planting and harvesting every 24 hours. However, in the equatorial region, problems in GNSS signal quality, due to interference from the ionosphere, have impeded the operation as recommended by manufacturers. The result has been the complete stoppage of the machines during certain periods of the year and at certain times (post-sunset hours) of day causing considerable economical losses and discrediting to the technology.
In support to air navigation, reference stations must have their coordinates determined very accurately. It is also necessary an effective control of system operation with immediate warning information to users in case of any failure (integrity).
To meet these requirements, complementary systems to GNSS have been designed and are currently in use. The International Civil Aviation Organization has classified these systems into two types, which can be applied in isolation or combined:
1. SBAS (space based augmentation systems, such as EGNOS and WAAS – cover large areas) this system is used to complement other satellite systems, e.g., GPS and/or GLONASS;
2. GBAS (ground based augmentation systems – local) – provide localized support such as in the vicinity of airports.
Due to the extreme ionospheric conditions observed in equatorial regions (i.e. in Brazil), the use of GBAS correction is encouraged because the SBAS is ineffective.
An example is the Galeão International Airport in Rio de Janeiro where a GBAS system purchased from Honeywell Aerospace is in the process of certification, which was installed and is currently being tested. If the system meets the expectations of the authorities, it should be adopted in other airports in Brazil.
Therefore, new algorithms that enable GNSS high accuracy positioning techniques and systems to mitigate the effects of the ionosphere, like the forecasting invention method, may contribute to improving the scenario for the use of GNSS and SBAS (EGNOS) in Brazilian civil aviation.
In conclusion, no method besides the proposed invention is currently able to give short-term forecast (from seconds to minutes) or longer forecast of the basic quantities describing ionospheric and signal propagation conditions in particular under severe scintillation environment. These quantities are necessary to feed mitigation algorithms to improve the performance of the real-time GNSS precise positioning techniques. The present invention method provides a deterministic forecasting, contrary to the traditional models based on statistical approaches: the computation of the velocity of the scalar field plays a key-role in the parameters forecasting.