Mat Churchill wrote:

Hi All,

Related to my query re real flight playback, I thought I should start at
the beginning. I found this mention here on the Avsim Flightgear forum
re playback.

I am already outputting NMEA data for use by Atlas. Can I record this to
disk somehow ?

Look at the docs-mini/README.IO file. It should show how to export the nmea data to a file (or serial port) rather than a net connection.

and if so could someone point me in the direction of
information on how to replay NMEA data in Flightgear.

Playback should also be mentioned in the README.IO file I think. I haven't played with file I/O in years though so I can't say for sure if it still works with no issues.

I'm also assuming that there is currently no way of inputing pitch, roll
& yaw data while playing back NMEA data ? if so would this be easy to

The NMEA format doesn't account for pitch/roll/yaw. I'm not sure we'd want to start modifying the format either. Probably the nicest solution (but would involve some effort) would be to write some offline tool that would take the saved NMEA data (probably at 1hz?) and do all the roll/pitch/yaw calculations and interpolate for 30 or 60 hz. Then you could feed this back to FG as FGNativeFDM structures and get nice smooth playback. (You could even feed FGNativeCtrls structures back too and animate the control surfaces if you want to estimate their positions.)

I found this paper on the web regarding generating accurate pitch, roll,
yaw, altitude, position & velocity data.

I think the end product derived from the above was this:

There are other papers out there from people such as creators of robot
football teams all tackling similar issues.

I spent the weekend digging around on the web and made some calls on
Monday and it appears the component cost could be as low as 300 - 400
to make a flight logger. One particular solid state gyro is mentioned as
cheap but good by everyone from amateur rocket clubs to R/C helicopter

However if you read the above document the real deal breaker re making a homemade flight logger is not the component cost, but the processing
of the signal from the gyros into accurate attitude / position data.

Yes that's hard ... I won't mention any names, but I've seen phd and master's level people struggle significantly with implimenting kalman filtering in a real world task. The theory itself is difficult enough, but getting a correct implimentation in your own code seems to be an order of magnitude harder. (Other's may disagree, I've never attempted to understand/impliment kahlman filtering myself, so I'm not speaking with much authority here ...) :-)

Someone more than at home with extended kalman filter formulae amongst
other things needs to write an algorithm to process the turn rate & gps
data into accurate attitude / position  data. From what the paper says
substantial testing would be required. This actually is rocket science !
and is way above my head ( at least 60 miles above my head )

I did think that at least with a flight logger rather than a real time
device you could record raw turn rate / gps data in flight and do all
the processing on your PC when you got home, not that that diminishes
the complexity of maths that would need doing.

If you want to just approximate roll/pitch/yaw based on gps data then you could always start simple, use a simple smoothing function, and at least get something working before you tackle more complex approaches.

If you need to process raw gyro output (accelerations) and translate those into accurate positions and orientations, then you probably need to dig into Kahlman filtering.

From what I've observed on this list it would be no surprise if some of
the readers do understand the principles of Kalman filters. Maybe some
of the information is already being shared by amateur rocketry, R/C
helicopter enthusiasts etc ?

Aaron Kahn (I don't know if that is quite the right name) was a guy on the list. He is the only person I've ever seen personally who's produced a successful kahlman filter implimentation in real computer code to run in real time on a real embeded computer.

I've seen a lot of people that can talk your ear off with the high level theory, or who know some of the basics of what Kahlman filtering does and what it's good for. But I've only seen one person who's managed to pull off a real world successful implimentation ... :-)

It will take a while, but I am building a simple GPS logger at the
moment. If anyone is interested in taking part in getting the gyro part
to work I could have it built here and post it out to others for

I'm interested ... along with 100 million other things ... but please keep us up to date on your ideas, questions, and progress.



Curtis Olson HumanFIRST Program
FlightGear Project
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