Brouwer-Lydanne conversion between mean and osculating Elements

I am trying to convert between osculating orbital elements and specifically Brouwer-Lydanne mean elements. I have thus far tried using the FiniteDifferentPropagatorConverter to create both a TLEPropagator and KeplerianPropagator based on the osculating elements I have, but neither has produced the Brouwer-Lydanne mean elements. I’ve also attempted to use the OsculatingToMeanElementsConverter, though that also did not produce the desired results.

This reference https://arc.aiaa.org/doi/abs/10.2514/4.867231 provides a first-order mapping algorithm to directly convert from osculating to specifically Brouwer-Lydanne mean elements. Is there anything currently like that in the Orekit library that I am missing?

Hi @rclubb ,

Using the propagator convertor to get the mean elements as you did is a proper way. Did you tried using the DSST propagator ?

Concerning the Brouwer-Lyddane method, we do not have yet this orbit propagator in Orekit. Implementing it is not really a complex task. Indeed, the reference paper for the Lyddane model is only 4 pages long. Adding this algorithm in Orekit would be a good addition.

If you would like to have it included, please open a feature request on the issue tracker.

Kind regards,
Bryan

Bryan,

Thanks for the response. I had tried the DSST propagator before, and I gave it another go today, both times I did not get the desired results. I am comparing my results against the output from an STK model, and I think there is just no getting around the fact that I need to use the Brouwer-Lydanne method. I will open a ticket to request this feature. Thanks for the help!

-Ryan

Hi Bryan
I see that has been fixed, is it going to be released in the next version of Orekit?
Thanks in advance and for the great work!
Alberto

Hi @alberto-ferrero

Yes, the issue has been fixed. It will be available in the next Orekit version that will be released in about two weeks. It is currently available in the development version of the library.

Best regards,
Bryan

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