The 5% error is comparing the reconstructed translation vector to the actual GPS measurements. I’m not sure how this may affect the attitude reconstruction but I do know from messing around with multi-variate optimization that removing variables from the problem should help me get a more accurate result -or at least a less degenerated one-.
I’m attacking this on several fronts, simultaneously trying to improve target localization but also trying to minimize other potential sources of error. I did seem reasonable to use all available information (the reliable GPS position information, in this case) to try and improve the result.
Given that I’m irrevocably on Python, I may need to look around at building the C++ source if it comes to it. I’ll need to assess which would take less time, build the source with minor changes or making an optimizer on my own. I think someone already had a similar problem before in the old opencv forum (see here) and might have solved it by modifying the source (?).
Thanks for the help, Steve! (and thanks to everyone else)