Data reduction routine in Python for the GPS/ Turn Regression/Orbis Method.
It uses an ordinary least squares method to solve for wind from GPS, altitude, airspeed and outside air temperature data collected during a stabilized level turn.
This video starts directly with coding in Python. If you are looking for the prequel, where the concepts are briefly explained, this is the link:
https://youtu.be/cWcys_DgYck
______Video Contents______
00:00 - Intro
01:20 - Preamble
03:25 - Flight test data loading
06:17 - Quick raw data plot
07:20 - Data quality check (statistics)
11:47 - Anemometric side / instruments calibration
13:20 - Mach
14:00 - True airspeed
14:16 - Wind triangle recap
15:17 - North / East components
15:47 - Quick Orbis plot
16:20 - Matrix build
18:28 - Pseudo-inverse solution
19:55 - Statsmodels alternative solution
21:16 - ANOVA analysis
22:51 - Wind speed / direction
23:44 - delta Ps / Ps
26:27 - FAR 25 compliance check
______Useful Links______
Part 3 - FAR 25 PEC Data Expansion in Python
https://youtu.be/W96lvjsy-68
Flight Test Channel Github's
https://github.com/flight-test-engineering
USAF TPS Textbook
https://ntrl.ntis.gov/NTRL/dashboard/searchResults/titleDetail/ADA170957.xhtml
AC 23-8C
https://www.faa.gov/documentlibrary/media/advisory_circular/ac_23-8c.pdf
Society of Flight Test Engineers
http://sfte.org/
http://sfte-ec.org/
JupyterLab
https://github.com/jupyterlab/jupyterlab
Python Basics
https://pythonprogramming.net/python-fundamental-tutorials/
https://www.youtube.com/playlist?list=PLQVvvaa0QuDeAams7fkdcwOGBpGdHpXln