A GPS-Based Pitot-Static Calibration Method Using Global Output Error Optimization

Abstract

Pressure-based airspeed and altitude measurements for aircraft typically require calibration of the installed system to account for pressure sensing errors such as those due to local flow field effects. In some cases, calibration is used to meet requirements such as those specified in Federal Aviation Regulation Part 25. Several methods are used for in-flight pitot-static calibration including tower fly-by, pacer aircraft, and trailing cone methods. In the 1990's, the introduction of satellite-based positioning systems to the civilian market enabled new inflight calibration methods based on accurate ground speed measurements provided by Global Positioning Systems (GPS). Use of GPS for airspeed calibration has many advantages such as accuracy, ease of portability (e.g. hand-held) and the flexibility of operating in airspace without the limitations of test range boundaries or ground telemetry support. The current research was motivated by the need for a rapid and statistically accurate method for in-flight calibration of pitot-static systems for remotely piloted, dynamically-scaled research aircraft. Current calibration methods were deemed not practical for this application because of confined test range size and limited flight time available for each sortie. A method was developed that uses high data rate measurements of static and total pressure, and GPSbased ground speed measurements to compute the pressure errors over a range of airspeed. The novel application of this approach is the use of system identification methods that rapidly compute optimal pressure error models with defined confidence intervals in nearreal time. This method has been demonstrated in flight tests and has shown 2-σ bounds of approximately 0.2 kts with an order of magnitude reduction in test time over other methods. As part of this experiment, a unique database of wind measurements was acquired concurrently with the flight experiments, for the purpose of experimental validation of the optimization method. This paper describes the GPS-based pitot-static calibration method developed for the AirSTAR research test-bed operated as part of the Integrated Resilient Aircraft Controls (IRAC) project in the NASA Aviation Safety Program (AvSP). A description of the method will be provided and results from recent flight tests will be shown to illustrate the performance and advantages of this approach. Discussion of maneuver requirements and data reduction will be included as well as potential applications.

Calibrating airborne measurements of airspeed, pressure and temperature using a Doppler laser air-motion sensor

“…If the wind is known accurately by independent measurement, the drift measured by GPS can be compared to the drift expected in the wind measured by the aircraft, and the associated dynamic pressure can be corrected to minimize the difference from the independent measurement of wind. Examples are discussed by Foster and Cunningham (2010) and by Martos et al (2011), where dynamic pressure was calibrated by comparing wind measured on the aircraft to that measured from a tethered balloon. GPS measurements have also been used without an independent reference, with flight manoeuvres and Kalman filtering, to calibrate dynamic pressure (Cho et al, 2011).…”

A Full-Envelope Air Data Calibration and Three Dimensional Wind Estimation Method Using Global Output-Error Optimization and Flight-Test Techniques

“…The calibration is modeled as a bias plus a gain based on the inverse of un-calibrated differential pressure as recommended in Ref. 6 and depicted in Fig. 3.…”

“…5 Dynamic maneuvers have been proposed and used in flight to calibrate static pressure over a range of airspeeds. 6,7 The proposed method in this paper makes extensions to this dynamic maneuver to include calibrating angle of attack and flank angle while taking into account vertical wind.…”

Subscale Flight Testing for Aircraft Loss of Control: Accomplishments and Future Directions

“…12 The method uses a global error method and GPS data to efficiently and accurately perform in-flight pitotstatic system calibration. Real-time winds-aloft monitoring, provided by a tethered aerostat, was used to aid in the validation of this method.…”