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Satellite Orbit Determination L1-467

GeodesyOrbital mechanicsδ=3 · standardL_DAG = 3.2📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

Satellite Orbit Determination: Satellite orbit determination: estimate initial state vector from tracking data (range, range-rate, angles) using batch or sequential processing. The forward operator produces the measurement through a 3-node primitive DAG (M.ode.equations_of_motion…); recovery is posed as a parameter_estimation problem. Difficulty tier delta=3 with effective condition number kappa_eff~200; atmospheric_drag_uncertainty, SRP_modeling_error set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

D.time -> S.kalman.orbit_filter -> O.least_squares.batch
D.timeS.kalman.orbit_filterO.least_squares.batch

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
5000

Existence of the recovered 6D_orbital_state_vector is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 200); atmospheric_drag_uncertainty dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Gaussian sets the irreducible data-fidelity floor.

Solvability C

Solver class:
sequential-filter [batch_least_squares or extended_Kalman_filter (SGP4 for TLE)]
Convergence rate q:
2
Complexity:
O(N_obs * N_state ** 2) for batch normal equations per iteration

Specs (0)

No L2 specs registered yet for this principle.