UAV Gust Rejection in Urban Turbulence

ISEF Category: Engineering Technology: Statics and Dynamics

Subcategory: Aerospace and Aeronautical Engineering  ·  Difficulty: Advanced  ·  Setup: University Lab  ·  Time: Full Year

The Hook

A small gust can push a drone off course faster than you can blink. That matters when a UAV flies near buildings, where air behaves like a messy, shifting maze. You can test that mess with fans, sensors, and careful flight logs. Your project can turn “feels stable” into real numbers.

What Is It?

This project looks at how a fixed-wing UAV handles turbulent air. Gust rejection means how well the aircraft stays on its path when the wind changes suddenly. Think of it like riding a bike on a smooth road versus a cobblestone street. The bike is the UAV, and the wind bumps are the gusts.

Urban-canyon turbulence happens when wind squeezes between buildings, wraps around corners, and breaks into uneven swirls. A Dryden gust spectrum is a math model that describes how gust strength changes across different sizes of turbulence. If your flight data matches that spectrum, you can compare different UAV designs, control settings, or flight speeds in a consistent way.

Why This Is a Good Topic

This is a strong science fair topic because you can change one thing at a time and measure the result with flight data. You can compare flight stability across different gust patterns, control gains, wing shapes, or airspeeds. The topic connects to real problems in delivery drones, inspection aircraft, and city flight safety. You also get to learn sensor logging, signal analysis, and model fitting, which are useful research skills.

Research Questions

• How does gust intensity affect roll, pitch, and yaw stability in a fixed-wing UAV?
• What is the effect of flight speed on the UAV's ability to reject short gusts?
• Does a change in control tuning reduce attitude error under the same turbulence pattern?
• To what extent do IMU logs and airspeed logs agree with a fitted Dryden gust spectrum?
• Which fan array layout produces turbulence that best matches urban-canyon flow signatures?
• How does blocked-grille fan configuration change the frequency content of the measured gust field?

Basic Materials

• Fixed-wing UAV or RC airplane with onboard flight controller and data logging.
• IMU sensor data logger or autopilot with exportable logs.
• Airspeed sensor or pitot tube module.
• 4 to 8 household box fans.
• Cardboard, foam board, or plywood panels for fan spacing and partial blockage.
• Measuring tape.
• Digital kitchen scale or load scale for setup checks.
• Tripod or fixed mount for a test camera.
• Laptop with spreadsheet software.
• Safety glasses and hearing protection.

Advanced Materials

• University wind tunnel or large indoor test bay.
• Research-grade motion capture system or high-rate inertial sensor package.
• Multi-hole probe or calibrated hot-wire anemometer.
• Programmable flight controller with tunable control gains.
• Data acquisition system with synchronized timestamps.
• CFD or turbulence analysis software.
• Calibration equipment for airspeed and inertial sensors.
• Structural test jig for repeatable airframe comparisons.
• High-speed camera for flow visualization.
• MATLAB or Python environment for signal processing.

Software & Tools

• Python: Processes IMU and airspeed logs, fits spectra, and plots flight response metrics.
• ImageJ: Measures flow visualization features from smoke or marker video frames.
• Logger viewer software: Exports and checks flight controller data for timing gaps and sensor noise.
• GNU Octave: Runs matrix calculations and curve fitting if you do not have MATLAB.
• QGroundControl: Reviews autopilot logs and helps confirm sensor settings before analysis.

Experiment Steps

1. Define the one response metric you will use first, such as roll variance, heading error, or control effort.
2. Map the turbulence source so you know which fan settings create repeatable gust patterns.
3. Choose a flight condition matrix that changes only one factor at a time, such as speed, control gain, or turbulence strength.
4. Plan a logging setup that synchronizes IMU data, airspeed data, and any video or flow measurements.
5. Build a baseline model for calm-air flight so you can compare gust cases against a clean reference.
6. Select the statistical test or spectral fit that will turn raw logs into a fair comparison across runs.

Common Pitfalls

• Treating fan output as identical across all positions, which makes the turbulence field uneven and hard to compare.
• Blocking fan grilles in a way that changes motor load from fan to fan, which alters the gust pattern between trials.
• Logging IMU and airspeed data with unsynced timestamps, which makes response timing look wrong.
• Comparing flights with different launch angles or trims, which hides the real effect of gusts.
• Fitting a Dryden spectrum to too little data, which makes the model look better than the measurement actually supports.

What Makes This Competitive

A strong version of this project does more than say whether the UAV shook less or more. You can compare multiple control settings, multiple turbulence signatures, and multiple response metrics, then test which one predicts flight performance best. You can also check whether your fan-built turbulence actually matches a Dryden-style model instead of assuming it does. That kind of careful measurement and analysis makes the work feel like real engineering research.

Project Variations

• Test how wing loading changes gust rejection by comparing two fixed-wing airframes with different mass distributions.
• Compare open-loop flight response versus tuned autopilot response under the same fan-generated turbulence.
• Replace the UAV with a glider-style airframe and analyze whether lower airspeed improves or worsens disturbance recovery.

Learn More

• NASA Technical Reports Server: Search for UAV gust response, Dryden turbulence, and fixed-wing flight stability papers.
• MIT OpenCourseWare, Aerodynamics: Find free lecture notes on lift, drag, stability, and control.
• NOAA Aircraft and Turbulence Resources: Look for background on atmospheric turbulence and wind measurement concepts.
• NASA Glenn Research Center: Read free educational pages on aircraft stability, control, and atmospheric effects.
• PubMed: Search for human factors or vibration-response papers if you want to connect turbulence to sensor and control performance.