I'm wondering how the physics models handle the state discontinuity if you're dropping intermediate telemetry. Typically those propagators rely on continuous integration steps, so if the buffer leaks data to catch up, I'd expect significant drift unless you're constantly re-seeding the state vector. How do you manage the handoff between the dropped data and the physics fallback without a jump in the prediction?
We prevent discontinuities by using a Continuous Extended Kalman Filter where the physics model serves as the persistent baseline and telemetry acts only as a corrective update. When the buffer leaks, the system doesn't snap to a new position; instead, it continues propagating the state via physics while the uncertainty covariance grows smoothly. When fresh data eventually arrives, we use the innovation delta to gradually steer the state back to reality, ensuring a seamless transition rather than a coordinate jump.
