Data Analytics + Flight Test

26 March 2023

Flight test has always been fueled by data analytics. Flight test takes a system into the unknown to explore and gather data. That data needs to be confirmed for quality, visualized, analyzed for patterns, and interpreted to inform decisions. So, while data analytics is nothing new in flight test, the last 10 to 15 years have seen major advancements in algorithms, programming frameworks, storage, parallel processing, and the use of graphics processing units (GPUs), resulting in what has been called “Big Data Analytics” in the financial and social media industries.

Changes in test instrumentation have pushed flight test teams closer and closer to the realm of “Big Data.” Flight data from a fully instrumented Airbus 380 or F-35 approaches the scale of banking or financial systems, whether "streaming" (real-time data monitored and analyzed on-the-fly either on-board or via telemetry) and "batch" (recorded, then made available later).

There are several different types of data analytics, including:

1. Exploratory: Viewing the data from multiple perspectives provides insight into data quality, outliers, anomalies, unexpected patterns, and suggestions for follow-on analysis.
2. Descriptive: Summarizing and describing data in order to understand what has happened within the dataset.
3. Diagnostic: Investigating the root cause of a problem or issue in order to understand why it occurred.
4. Predictive: Creating statistical models and machine learning algorithms to predict future outcomes or trends based on available data.
5. Prescriptive: Using data and analytics to recommend specific actions or decisions.

Data analytics allows professional flight testers to make data-informed decisions, rather than only relying on heuristics or prescriptive processes.

Python is the preferred tool for data analytics, with a number of libraries and frameworks that are specifically designed for data analysis. These libraries, including NumPy, SciPy, and pandas, provide a range of tools for tasks such as importing and cleaning data, manipulating data sets, and building and evaluating statistical models. Python is widely used in the field of machine learning, which is a subset of data analytics that involves using algorithms to automatically learn patterns in data and make predictions. There are many machine learning libraries available in Python, such as TensorFlow and scikit-learn, which make it a powerful choice for this type of work.

Python has several advantages over MATLAB for data analytics and visualization:

1. Cost: Python is an open-source language, which means it is freely available to use and modify. In contrast, MATLAB is a proprietary language and requires a license to use, which can be expensive.
2. Community and resources: Python has a large and active community of users and developers, which means there is a wealth of online resources, documentation, and support available. MATLAB also has a large user base, but it is not as widespread as Python.
3. Extensibility: Python is a general-purpose programming language, which means it can be used for a wide range of tasks beyond data analytics and visualization. This makes it a more versatile tool than MATLAB, which is primarily focused on technical computing.
4. Libraries and frameworks: Python has a large number of libraries and frameworks that are specifically designed for data analysis and visualization, such as NumPy, pandas, and Matplotlib. These libraries provide a range of tools for tasks such as importing and cleaning data, manipulating data sets, and creating charts and plots. MATLAB also has a number of built-in functions and toolboxes for data analysis and visualization, but the range of options is not as extensive as in Python.

Large datasets demand a versatile tool, and Python can be that tool for your test team! Make it a valuable addition to your flight test toolkit.


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About the Author

Instructor Flight Test Engineer Nathan Cook

Nathan Cook is a graduate of the US Air Force Test Pilot School, with experience planning, flying, and directing hundreds of flight test missions for military projects from the cockpit and the control room. From 2011 to 2013, he served at the US Air Force Test Pilot School as airborne and control room Instructor Flight Test Engineer, Flying Qualities Branch Chief, Test Conductor Standards and Evaluation, Unit Test Safety Officer, and Certified Flight Instructor Glider Pilot qualified in all glider curriculum rides including spin training. From 2013 to 2015, he was the lead flight test engineer for all USAF F-16 mission systems software flight test. He has served as the Chief Test Engineer for a fighter flight test squadron, responsible for all technical and safety aspects of projects across multiple fighter types and systems, as well as control room training and evaluation. Nathan is a Senior Member of the Society of Flight Test Engineers, and currently serves as the Chief Data Officer at the group level, bringing modern tools and techniques to the test mission. He holds a Masters degrees in Education, Mechanical Engineering, Flight Test Engineering, and Analytics, and a B.Sci. Physics with a concentration in German. He also holds Private Pilot - Single Engine Land and Commercial - Glider certificates, is a Certified Flight Instructor - Glider, and has logged time in over 30 different types of aircraft. His publications include "Flight Test Brevity," "Data Hackathons: Jumpstarting Your Test Organization's Digital Transformation," “A Blank Slate: Redefining F-16 Flight Test,” and "Lessons Learned During Development of a Hands-On Unmanned Aerial Vehicle Flight Test and Evaluation Training Course."

Instructor Flight Test Engineer Saint .

“Saint” is a Flight Test Engineer and Test Pilot School graduate. He has 10 years of flight test experience on prototype aircraft , weapon integration , avionics and electronic warfare system testing, with extensive hands-on experience in data acquisition systems. He is an artificial intelligence and machine learning enthusiast, with many data analytics projects for flight testing. He has flown almost 25 types of fixed wing aircraft.

Instructor Test Pilot David Kern

David Kern is a graduate of the US Air Force Test Pilot School, with experience planning and flying hundreds of flight test missions for civil aircraft certification and military projects. He is an Associate Fellow with the Society of Experimental Test Pilots and Member of the Society of Flight Test Engineers. In his USAF career, he was the USAF F-16 project test pilot for the Collier Trophy-winning Automatic Ground Collision Avoidance System (AGCAS) and served as Instructor Test Pilot and Director of Operations at the USAF Test Pilot School, teaching all parts of the multi-engine and fighter curricula. In civil flight test, he served as a flight test pilot for the Aircraft Certification Service with the Federal Aviation Administration, and is currently a Flight Test Captain for a major airline. He holds a Master of Science in Flight Test Engineering and B.Sci. Electrical Engineering with a minor in Mathematics. He also holds an Airline Transport Pilot certificate with eight type ratings, is an active Certified Flight Instructor for instrument conditions, and has logged piloting time at the flight controls of over 80 different types of aircraft. His publications include "Flight Test Techniques for Active Electronically Scanned Array (AESA) Radar", "Accelerated Development of Flight Tested Sensors and Systems", and “Introduction to Fly-by-Wire Flight Control Systems: The professional pilot’s guide to understanding modern aircraft controls.”