How Is True Wind Speed and Wind Direction Derived from an Ultrasonic Anemometer?

Technical Article | UAV Sensors · Mobile Weather Stations · Meteorological Observation

When an ultrasonic anemometer is mounted on a moving platform such as a UAV, drone, or vehicle, the measured wind vector contains the influence of the platform’s own motion. To obtain the true wind speed and wind direction, the ultrasonic anemometer system must incorporate an electronic compass, gyroscope/attitude sensor, and GPS or BeiDou positioning module. The measured data then needs to be corrected through a sequence of coordinate transformations and vector calculations: first, the platform velocity is transformed from the geographic coordinate system into the body coordinate system; next, the true wind vector is calculated in the body frame; the result is transformed back into the geographic frame; finally, horizontal wind speed and wind direction are calculated.

Figure 1. Reference image for the mobile ultrasonic anemometer configuration. Source: 

The following sections describe the theory and algorithm for deriving true wind speed and true wind direction from an ultrasonic anemometer installed on a moving platform, including coordinate definitions, input data, correction steps, and calculation formulas.

1. Coordinate System Definitions

1.1 Geographic Coordinate System (NED)

The origin is located at the platform’s center of mass. The X-axis points North (N), the Y-axis points East (E), and the Z-axis points Down (D), with downward defined as positive. This coordinate system is used to describe the absolute direction of the wind vector and the platform velocity.

1.2 Body Coordinate System (FRD)

The origin is located at the anemometer mounting point. The X-axis points Forward (F, the platform nose direction), the Y-axis points Right (R), and the Z-axis points Down (D). This frame is consistent with the measurement coordinate system of the ultrasonic anemometer.

1.3 Attitude Angles

The platform attitude is represented using Euler angles, with the rotation sequence defined as yaw (ψ), pitch (θ), and roll (φ).

• Yaw angle ψ: the clockwise angle from geographic North to the horizontal projection of the platform longitudinal axis (nose direction), ranging from 0° to 360°.

• Pitch angle θ: the angle between the platform longitudinal axis and the horizontal plane; nose-up is positive.

• Roll angle φ: the rotation of the platform about its longitudinal axis; right roll is positive.

2. Input Data

2.1 Ultrasonic Anemometer Velocity in the Body Frame (FRD)

Vmeas = (umeas, vmeas, wmeas)

2.2 Platform Velocity from GPS/BeiDou in the Geographic Frame (NED)

VGPS = (vN, vE, vD), where vD is positive downward.

2.3 Platform Attitude

Yaw ψ, pitch θ, and roll φ, provided by the attitude sensor in radians.

3. Algorithm for Calculating True Wind Speed and Wind Direction

Step 1: Express Platform Velocity in the Body Coordinate System

Construct the rotation matrix RN2B that transforms a vector from the geographic coordinate system (NED) to the body coordinate system (FRD):

RN2B = Rx(φ) Ry(θ) Rz(ψ)

Rotation-matrix reference image:

Step 2: Calculate the True Wind Vector in the Body Coordinate System

True-wind-vector calculation reference image:

Step 3: Transform the True Wind Vector to the Geographic Coordinate System (NED)

Geographic-coordinate transformation reference image:

Step 4: Calculate Horizontal Wind Speed and Wind Direction

Horizontal wind-speed and wind-direction calculation reference image: 

4. Key Considerations and Conclusion

• Attitude compensation: The rotation-matrix approach incorporates the effects of platform pitch and roll on wind speed and wind direction, so no separate attitude-correction step is required.

• Coordinate-system consistency: If GPS outputs velocity in the East-North-Up (ENU) frame as (vE, vN, vU), convert it to NED as follows: vN remains unchanged, vE remains unchanged, and vD = −vU.

• Time synchronization: Measurements from the ultrasonic anemometer, GPS/BeiDou receiver, and attitude sensor should be time-synchronized to minimize motion-related errors.

• Electronic compass: The yaw angle ψ should be obtained from an electronic compass and corrected for magnetic declination so that the heading is referenced to true North.

By applying vector operations and coordinate transformations, the system can directly derive the true wind vector and true wind direction measured from an ultrasonic anemometer on a moving platform. The method is theoretically rigorous and is applicable to wind measurement and motion compensation on UAVs, drones, vehicles, and other mobile platforms.

5. Application Perspective for HONGYUV Mobile Meteorological Sensing

For mobile meteorological observation, separating platform motion from the ambient wind field is essential. An ultrasonic anemometer integrated with GPS/BeiDou positioning and attitude sensing can form a compact wind-measurement subsystem for UAV-based atmospheric observation, vehicle-mounted mobile weather stations, and other dynamic environmental-monitoring platforms.

HONGYUV Technology’s product portfolio includes Meteo Sensors, Mobile Weather Stations, UAV Sensors, Traffic Environment Sensors, Industrial Instruments, and Accessories. The motion-compensation principle described in this article is especially relevant to UAV Sensors and Mobile Weather Stations, where the measurement platform is continuously moving and changing attitude.

In practical system integration, final wind-measurement performance depends not only on the ultrasonic sensing element, but also on sensor alignment, coordinate conventions, GPS/BeiDou accuracy, attitude estimation, time synchronization, installation geometry, and the motion-compensation algorithm. These factors should be considered together when developing OEM/ODM meteorological sensing equipment.

6. Technical Keywords

Ultrasonic anemometer; true wind speed; true wind direction; motion compensation; wind-vector correction; NED coordinate system; FRD body frame; Euler angles; yaw; pitch; roll; GPS; BeiDou; UAV wind measurement; mobile weather station; meteorological sensors.