dsgp4 v1.1.3

Small bug fix in batch propagation, when initialized=False

dsgp4 v1.1.2

In this release we introduce ML-dSGP4 in the module, with tutorials.

dsgp4 v0.1.2

A new release fixing a couple of things:

• a better handling of an internal exception
• a minor fix for an unused variable

v1.0.1: Merge pull request #12 from esa/kepler_equation

Added a tolerance check in Kepler's equation (as per original SGP4 implementation) to prematurely exit in case it converges: this should improve the performance for most of cases.

dsgp4 v1.0.0

This release improves the dsgp4 batching, which was not working as efficiently as it should be, due to some operations being performed in the propagate_batch, instead of in the initialization part. As a result of this, a few breaking modifications to the way batches are initialized and batch propagation is performed were made. In particular:

• initialize_tle now also returns an extra output (the tle_batch), when a list of tles is passed as input
• that tle_batch must be used in the propagate_batch function: in this way, proper batch parallelization is done

Tests & docs have also been updated accordingly.

dsgp4 v0.1.2

This release improves the dsgp4 API (providing easier API to propagate TLEs both in normal and batch mode) and introduces several tutorials for its use.

Basic tutorials focusing on:

• what a TLE object is, how to load TLE objects, and how to construct them from strings or dictionaries
• how to propagate TLEs (both in batch and normal mode, and single or multiple times)
• how to compute partial derivatives of SGP4 outputs w.r.t. inputs and/or TLE parameters, leveraging the autodiff support

Advanced tutorials focusing on spaceflight mechanics problems:

• similarity transformation (i.e., covariance transformation)
• 1st order covariance propagation
• gradient-based optimization

dsgp4 v0.0.3

First dSGP4 release:

• SGP4 behavior + differentiability w.r.t. inputs and parameters
• TLE class & utils to easily interface with, parse, and create TLE data
• batch propagation (across different TLEs) with CPU & GPU support