Synthetic air data system
SADS estimates air data without direct measurement using other sensors.
A synthetic air data system (SADS) estimates flight information like airspeed, angle of attack, and angle of sideslip without using direct measurement sensors. Instead, it relies on data from GPS, wind estimates, the aircraft’s attitude, and its aerodynamic characteristics. While air data normally includes altitude, pressure, temperature, and Mach number, existing SADS designs mainly focus on the three quantities of airspeed, angle of attack, and angle of sideslip. The system serves as a monitor for the primary air data system when sensor or system faults occur, and it can also function as a backup for any aerial vehicle.
The concept of SADS dates back to the 1980s. Early work used vehicle dynamics models—often called aerodynamic model-based SADS—to estimate air data for both aircraft and spacecraft. However, this approach proved difficult because accurate vehicle dynamics models are hard to obtain. More recently, model-free SADS has been proposed, which does not require such models but instead depends on the accuracy of the inertial navigation system and three-dimensional wind estimates. Interest in SADS increased after the 2009 Air France Flight 447 accident, and later after the two Boeing 737 MAX accidents in 2018 and 2019. Research has been conducted by institutions such as the University of Minnesota, Delft University of Technology, NASA Langley Research Center, and the Technical University of Munich. Patents have been filed by Collins Aerospace and Honeywell. Synthetic airspeed, in particular, has become a focus for improving Boeing aircraft safety.
SADS provides analytical redundancy, adding an extra layer of safety to mechanical systems like pitot-static tubes and angle vanes. It can also detect failures in other subsystems through data compatibility checks. On the Boeing 787, a synthetic airspeed is calculated using angle of attack, inertial data, lift coefficient, and aircraft mass, helping the aircraft recover from erroneous airspeed readings. For unmanned aerial vehicles, SADS is valuable because low-cost air data systems on small drones are often unreliable, and adding multiple sensors is impractical due to size, weight, and power limits. SADS can improve drone reliability in both line-of-sight and beyond visual line-of-sight operations.
- Primary quantities estimated
- airspeed, angle of attack, angle of sideslip
- First concept decade
- 1980s
- Notable accidents raising interest
- Air France Flight 447 (2009), Lion Air Flight 610 (2018), Ethiopian Airlines Flight 302 (2019)
- Example aircraft with implementation
- Boeing 787
- Example research institutions
- University of Minnesota, Delft University of Technology, NASA Langley Research Center, Institute of Flight Mechanics and Flight Control at the Technical University of Munich
- Example companies filing patents
- Collins Aerospace, Honeywell
Lore & Background
The idea of SADS has been around since the 1980s. The basic idea is to use non air data sensors such as inertial measurement unit (IMU) and GPS fused with vehicle dynamics models to estimate the air data triplet: airspeed, angle of attack, and angle of sideslip. Most earlier work used vehicle dynamics models, an approach sometimes referred to as aerodynamic model-based SADS. However, this approach is challenging to implement because it is difficult to obtain accurate vehicle dynamics models possessing the fidelity needed to yield the required accuracy in the air data estimates. To address this issue, model-free SADS has been proposed recently, which does not require vehicle dynamics models but instead relies on the accuracy of the Inertial navigation system (INS) and Three-Dimensional (3D) wind estimates.
SADS has gained a lot of renewed interest after the Air France Flight 447 accident in 2009. Several universities and government agencies have been researching SADS related topics. Recent patents related to SADS have been filed by leading air data system producers such as Collins Aerospace and Honeywell. Moreover, the recent two Boeing 737 MAX accidents (Lion Air Flight 610 and Ethiopian Airlines Flight 302) have brought SADS into the spotlight again, with synthetic airspeed becoming a focal point to improve Boeing aircraft's safety.
SADS has been implemented in some advanced modern commercial aircraft such as the Boeing 787, where it calculates a synthetic airspeed from angle of attack measurement, inertial data, accurate lift coefficient, and aircraft mass. This synthetic airspeed has helped the Boeing 787 recover from erroneous airspeed measurement. SADS has also been implemented for unmanned aerial vehicles (UAVs), motivated by the fact that most low-cost air data systems on small Unmanned Aircraft Systems are not reliable, and having multiple air data sensors on small UAVs is not feasible due to stringent size, weight, and power constraints.
Reader's Guide
SADS is significant as a means to create analytical redundancy for mechanical air data systems such as pitot-static systems and angle vanes, potentially reducing risk. It can also be used to detect failures of other subsystems through data compatibility checks. The system's ability to estimate the air data triplet—airspeed, angle of attack, and angle of sideslip—using non-air data sensors provides a backup when primary sensors fail or produce anomalous readings. Its legacy is tied to major aviation accidents: the Air France Flight 447 accident in 2009 sparked renewed research, and the Boeing 737 MAX accidents in 2018 and 2019 further highlighted its importance, particularly for synthetic airspeed to improve safety. In commercial aviation, the Boeing 787 already uses synthetic airspeed to recover from erroneous measurements. For UAVs, SADS can significantly increase overall reliability in both line-of-sight and beyond visual line-of-sight operations, addressing the unreliability of low-cost air data systems and the constraints of size, weight, and power. Recent academic research has focused on improving SADS's accuracy, fault detectability, and reliability for small UAS.
Did You Know?
- SADS can estimate airspeed, angle of attack, and angle of sideslip without directly measuring air data.
- The concept of SADS has existed since the 1980s.
- The Boeing 787 uses synthetic airspeed calculated from angle of attack, inertial data, lift coefficient, and aircraft mass.
- Model-free SADS relies on the accuracy of the Inertial navigation system and 3D wind estimates, not vehicle dynamics models.
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