Enums

enums

ARCorrelation

Strategy for correlating two propagated hypothesis clouds.

Construct via the variant-specific classmethods rather than __init__: particle_mahalanobis, joint_fit_chi_squared, and gmm. default returns ParticleMahalanobis { gate_chi2=16.0 }.

__repr__()

Returns a constructor-style call carrying the variant parameters, e.g. ARCorrelation.particle_mahalanobis(gate_chi2=…).

__str__()

Returns the bare variant name (same string as get_name).

default() classmethod

Returns the balanced default (ParticleMahalanobis with gate_chi2=16.0).

Returns:

Name	Type	Description
ARCorrelation	ARCorrelation	The default strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of "ParticleMahalanobis", "JointFitChiSquared",
	str	"GMM".

gmm(n_components, gate_distance) classmethod

Gaussian-mixture-model correlation via Bhattacharyya distance.

Parameters:

Name	Type	Description	Default
n_components	int	Number of mixture components fit per cloud [count; >= 1].	required
gate_distance	float	Bhattacharyya-distance gate [dimensionless; > 0].	required

Returns:

Name	Type	Description
ARCorrelation	ARCorrelation	The configured strategy.

joint_fit_chi_squared(gate_chi2, max_pairs) classmethod

Joint batch-least-squares fit on both tracklets' observations scored by post-fit chi-squared.

Parameters:

Name	Type	Description	Default
gate_chi2	float	Chi-squared gate on the post-fit weighted residual chi-squared [dimensionless; > 0].	required
max_pairs	int	Maximum number of (a, b) particle pairs to attempt the joint fit on per tracklet pair [count; > 0].	required

Returns:

Name	Type	Description
ARCorrelation	ARCorrelation	The configured strategy.

particle_mahalanobis(gate_chi2) classmethod

Pairwise Mahalanobis-distance correlation between propagated hypothesis-cloud particles.

Parameters:

Name	Type	Description	Default
gate_chi2	float	Chi-squared gate on the combined-covariance Mahalanobis distance squared [dimensionless; > 0].	required

Returns:

Name	Type	Description
ARCorrelation	ARCorrelation	The configured strategy.

AdmissibleRegionSampling

Strategy for sampling admissible-region particles from the (ρ, ρ̇) bounds attached to an angles-only TrackletFit.

Construct via the variant-specific classmethods rather than __init__: quasi_monte_carlo, grid, and adaptive. default returns the balanced QuasiMonteCarlo { n_particles=256 } default.

__repr__()

Returns a constructor-style call carrying the variant parameters, e.g. AdmissibleRegionSampling.quasi_monte_carlo(n_particles=…).

__str__()

Returns the bare variant name (same string as get_name).

adaptive(coarse_particles, refinement_particles) classmethod

Two-stage sampling: an initial coarse Halton sample, then a refinement sample concentrated near the admissible-region boundary.

Parameters:

Name	Type	Description	Default
coarse_particles	int	Coarse Halton-sample particle count [count; > 0].	required
refinement_particles	int	Additional refinement particles [count; >= 0].	required

Returns:

Name	Type	Description
AdmissibleRegionSampling	AdmissibleRegionSampling	The configured strategy.

default() classmethod

Returns the balanced default (QuasiMonteCarlo with n_particles=256).

Returns:

Name	Type	Description
AdmissibleRegionSampling	AdmissibleRegionSampling	The default strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of "QuasiMonteCarlo", "Grid", "Adaptive".

grid(n_rho, n_rho_dot) classmethod

Rectangular grid of n_rho × n_rho_dot points in the (ρ, ρ̇) plane.

Parameters:

Name	Type	Description	Default
n_rho	int	Number of ρ samples [count; > 0].	required
n_rho_dot	int	Number of ρ̇ samples [count; > 0].	required

Returns:

Name	Type	Description
AdmissibleRegionSampling	AdmissibleRegionSampling	The configured strategy.

quasi_monte_carlo(n_particles) classmethod

Halton-sequence quasi-Monte-Carlo sample of n_particles points in the (ρ, ρ̇) plane, restricted to the physical admissible region.

Parameters:

Name	Type	Description	Default
n_particles	int	Number of particles to retain after rejection-filtering on the admissible-region bounds [count; > 0].	required

Returns:

Name	Type	Description
AdmissibleRegionSampling	AdmissibleRegionSampling	The configured strategy.

AssociationConfidence

Confidence level for an observation-to-object association.

Numeric values increase with confidence: Low=0, Medium=1, High=2.

Attributes:

Name	Type	Description
High	AssociationConfidence	Strong match across multiple metrics; association is reliable.
Medium	AssociationConfidence	Partial or ambiguous match; should be reviewed before acting on.
Low	AssociationConfidence	Weak or speculative match; treat with caution.

__repr__()

Returns AssociationConfidence('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this confidence level.

Returns:

Name	Type	Description
str	str	One of "High", "Medium", "Low".

get_value()

Returns the integer code for this confidence level.

Returns:

Name	Type	Description
int	int	Low=0, Medium=1, High=2.

CDMCovarianceMethod

How a CDM object's covariance was produced (COVARIANCE_METHOD).

Attributes:

Name	Type	Description
Calculated	CDMCovarianceMethod	Covariance computed from the orbit determination.
Default	CDMCovarianceMethod	A default covariance was substituted.

__repr__()

Returns CDMCovarianceMethod('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the CDM string token of this value.

Returns:

Name	Type	Description
str	str	"CALCULATED" or "DEFAULT".

CDMManeuverable

Whether a CDM object is maneuverable (MANEUVERABLE).

Attributes:

Name	Type	Description
Yes	CDMManeuverable	The object can maneuver.
No	CDMManeuverable	The object cannot maneuver.
NotApplicable	CDMManeuverable	Unknown or not applicable; its string name is "N/A".

__repr__()

Returns CDMManeuverable('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the CDM string token of this value.

Returns:

Name	Type	Description
str	str	One of "YES", "NO", "N/A".

CelestialBody

A celestial body whose gravitational and positional models are available in this library.

Provides a unified dispatch surface over Earth, Sun, and Moon for force-model and ephemeris calculations. Earth's position is always the inertial origin (zero vector).

Attributes:

Name	Type	Description
Earth	CelestialBody	The Earth; position is always the inertial origin (0.0, 0.0, 0.0) [km].
Sun	CelestialBody	The Sun; position derived from a low-precision analytical model [km].
Moon	CelestialBody	The Moon; position derived from a low-precision analytical model [km].

__repr__()

Returns CelestialBody('…').

__str__()

Returns the bare variant name (same string as get_name).

equatorial_radius()

Returns the equatorial radius of this body.

Returns:

Name	Type	Description
float	float	Equatorial radius [km].

get_name()

Returns the string name of this celestial body.

Returns:

Name	Type	Description
str	str	One of "Earth", "Sun", "Moon".

get_position_at_epoch(epoch, priority)

Returns the inertial position of this body at the given epoch.

Earth always returns the zero vector. Sun and Moon positions are computed via low-precision analytical models; the accuracy of the result depends on the chosen PerformancePriority.

Parameters:

Name	Type	Description	Default
epoch	ModifiedJulianDate	Epoch at which to compute the position.	required
priority	PerformancePriority	Controls accuracy vs. speed of the underlying model.	required

Returns:

Type	Description
tuple[float, float, float] | None	tuple[float, float, float] | None: Inertial position (x, y, z) [km] in the J2000 / ECI frame, or None if the body's ephemeris model cannot produce a value at the requested epoch.

get_third_body_acceleration(position_sat, position_third_body)

Returns the third-body gravitational acceleration exerted on a satellite.

Uses the standard third-body perturbation formula with the gravitational parameter (μ) of the selected body.

Parameters:

Name	Type	Description	Default
position_sat	tuple[float, float, float]	Satellite position in the inertial frame (x, y, z) [km].	required
position_third_body	tuple[float, float, float]	Third-body position in the same inertial frame (x, y, z) [km].	required

Returns:

Type	Description
tuple[float, float, float]	tuple[float, float, float]: Acceleration (ax, ay, az) due to the third-body perturbation [km/s²].

CitraObservationType

Sensor modality of a Citra observation.

The string value (returned by get_value) is the lowercase serde serialisation used in JSON payloads.

Attributes:

Name	Type	Description
Optical	CitraObservationType	Passive optical measurement (right ascension / declination angles).
Radar	CitraObservationType	Active radar measurement (range and/or range-rate).
Doa	CitraObservationType	Direction-of-arrival (DOA) RF measurement (azimuth / elevation angles).

__repr__()

Returns CitraObservationType('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the display name of this observation type.

Returns:

Name	Type	Description
str	str	One of "Optical", "Radar", "Doa".

get_value()

Returns the lowercase serde serialisation string for this observation type.

Returns:

Name	Type	Description
str	str	One of "optical", "radar", "doa".

Classification

Data classification level for observation and orbit products.

Numeric values increase with sensitivity: Unclassified=0, Confidential=1, Secret=2.

Attributes:

Name	Type	Description
Unclassified	Classification	Publicly releasable data.
Confidential	Classification	Sensitive data restricted to authorised personnel.
Secret	Classification	Highly sensitive data with strict access controls.

__repr__()

Returns Classification('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this classification level.

Returns:

Name	Type	Description
str	str	One of "Unclassified", "Confidential", "Secret".

get_value()

Returns the integer code for this classification level.

Returns:

Name	Type	Description
int	int	Unclassified=0, Confidential=1, Secret=2.

CovarianceType

Coordinate basis in which a state covariance matrix is expressed.

Three variants are supported:

• Inertial(frame) — Earth-centered inertial Cartesian covariance, parameterised by which inertial ReferenceFrame the matrix is expressed in. Must be one of TEME, J2000, or GCRS. Constructed via the static method CovarianceType.Inertial(ReferenceFrame.TEME).
• Relative — RIC (Radial-In-track-Cross-track) local frame defined by the reference state's r, v. Accessed as the class attribute CovarianceType.Relative.
• Equinoctial — covariance in equinoctial element space [a, h, k, p, q, L]. Accessed as the class attribute CovarianceType.Equinoctial.

Attributes:

Name	Type	Description
Relative	CovarianceType	Covariance in the RIC (Radial-In-track-Cross-track) relative frame [km, km/s].
Equinoctial	CovarianceType	Covariance in equinoctial element space.

Inertial(frame) staticmethod

Constructs an Inertial covariance-type tag parameterised by the specific inertial frame.

Parameters:

Name	Type	Description	Default
frame	ReferenceFrame	One of ReferenceFrame.TEME, ReferenceFrame.J2000, or ReferenceFrame.GCRS.	required

Returns:

Type	Description
CovarianceType	An Inertial(frame) tag.

Raises:

Type	Description
ValueError	If frame is ITRF, PEF, or RIC — those are not inertial Cartesian frames.

__repr__()

Returns CovarianceType('…').

__str__()

Returns the bare variant name (same string as get_name).

get_inertial_frame()

Returns the embedded inertial ReferenceFrame for the Inertial variant, or None for Relative / Equinoctial.

Returns:

Type	Description
ReferenceFrame | None	The embedded frame for the Inertial variant, otherwise
ReferenceFrame | None	None.

get_name()

Returns the string name of this covariance type.

Returns:

Name	Type	Description
str	str	"Inertial(<frame>)" for an Inertial variant,
	str	"Relative" or "Equinoctial" otherwise.

get_value()

Returns the integer code for this covariance type.

The mapping is lossy for the Inertial variant: every embedded frame returns 0. Use get_inertial_frame to recover the specific inertial frame.

Returns:

Type	Description
int	0 for any Inertial(_), 1 for Relative, 2 for
int	Equinoctial.

is_inertial()

Returns True if this tag is the Inertial variant.

Returns:

Type	Description
bool	True for Inertial(_), False otherwise.

CoverageMetric

Scalar scored at each candidate location when mapping sensor coverage.

Selects how a candidate site's observability of a satellite or constellation is reduced to a single number for a CoverageGrid. Every variant is derived from the same access windows, so switching metric re-propagates nothing. The default variant is UniqueSatellitesCovered.

Attributes:

Name	Type	Description
UniqueSatellitesCovered	CoverageMetric	Count of distinct satellites with at least the required number of access windows (default). On a single satellite this degenerates to 0/1.
PassCount	CoverageMetric	Total number of access windows across all satellites.
TotalAccessTime	CoverageMetric	Summed access-window duration across all satellites [s].
MultiSensorCoverage	CoverageMetric	Superadditive co-detection score for multi-sensor placement - each satellite contributes k + bonus*C(k,2) where k is the number of placed sensors that see it, rewarding co-detection (e.g. radar and telescope) over the UniqueSatellitesCovered union. Used by optimize_sensor_locations with its co_detection_bonus.
UniqueThenAccessTime	CoverageMetric	Lexicographic custody objective - maximize the number of distinct covered satellites first, then break ties by the summed access duration over the covered satellites [s]. Answers "where do I see all of them, for as long as possible?" when many sites cover the same set. The per-site grid value is that covered-target dwell.
TotalVisibilitiesThenAccessTime	CoverageMetric	Like UniqueThenAccessTime but for placing several sensors it sums each sensor's covered-satellite count instead of unioning (a target seen by two sensors counts twice), tie-broken by summed covered dwell. Keeps every sensor's collection opportunities in the objective so a near-omniscient sensor cannot skew the placement toward sites that serve only it. On a single sensor it matches UniqueThenAccessTime; the per-site grid value is the covered count.

__repr__()

Returns CoverageMetric('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this coverage metric.

Returns:

Name	Type	Description
str	str	One of "UniqueSatellitesCovered", "PassCount", "TotalAccessTime", "MultiSensorCoverage", "UniqueThenAccessTime", "TotalVisibilitiesThenAccessTime".

DevicePreference

Controls whether batch propagation runs on CPU, GPU, or selects automatically.

The default variant is CPU.

Attributes:

Name	Type	Description
CPU	DevicePreference	Force CPU-only execution via the rayon thread pool (default).
GPU	DevicePreference	Force GPU execution via wgpu. The propagator raises RuntimeError when the gpu feature is disabled or no compatible adapter is found at propagation time.
Auto	DevicePreference	Automatic selection based on workload size; falls back to CPU for small batches.

__repr__()

Returns DevicePreference('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this device preference.

Returns:

Name	Type	Description
str	str	One of "CPU", "GPU", "Auto".

DragModel

Atmospheric density model used to compute aerodynamic drag acceleration.

Models range from the simplest (constant B* ballistic) through tabulated density profiles to empirical thermospheric models driven by solar and geomagnetic activity.

Attributes:

Name	Type	Description
Ballistic	DragModel	Constant ballistic coefficient (B*) drag; atmospheric density is absorbed into the coefficient.
Exponential	DragModel	Exponential density model with tabulated scale-height and base-density layers.
HarrisPriester	DragModel	Harris-Priester tabulated model with diurnal bulge correction.
NRLMSISE00	DragModel	NRLMSISE-00 empirical model; accounts for solar flux (F10.7) and geomagnetic activity (Ap).
JacchiaRoberts71	DragModel	Jacchia-Roberts 1971 semi-analytic model driven by exospheric temperature derived from F10.7 and Ap.
JacchiaBowman2008	DragModel	Jacchia-Bowman 2008 (JB2008) model; uses additional solar and geomagnetic indices (S10, M10, Y10).

__repr__()

Returns DragModel('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this drag model.

Returns:

Name	Type	Description
str	str	One of "Ballistic", "Exponential", "HarrisPriester", "NRLMSISE00", "JacchiaRoberts71", "JacchiaBowman2008".

get_value()

Returns the integer code for this drag model.

Returns:

Name	Type	Description
int	int	Ballistic=0, Exponential=1, HarrisPriester=2, NRLMSISE00=3, JacchiaRoberts71=4, JacchiaBowman2008=5.

EarthGravityModel

Earth spherical-harmonic gravity model.

Selects the set of gravitational coefficients (Stokes coefficients C and S) and associated constants (μ, equatorial radius) used by the force model and Keplerian element conversions.

Attributes:

Name	Type	Description
EGM96	EarthGravityModel	Earth Gravitational Model 1996; complete to degree and order 360. Used as the reference model for the XP propagator and osculating elements.
EGM2008	EarthGravityModel	Earth Gravitational Model 2008; complete to degree and order 2190. Higher resolution than EGM96; useful for precise force-model computation at low altitudes.
WGS84	EarthGravityModel	World Geodetic System 1984 gravity model; four-coefficient ellipsoidal approximation. Paired with WGS72-compatible SGP4/SDP4 constants for TLE-based propagation.

__repr__()

Returns EarthGravityModel('…').

__str__()

Returns the bare variant name (same string as get_name).

earth_model()

Returns the static EarthModel for this gravity model.

The model is loaded once at startup and stored as a static reference; calling this method is zero-allocation.

Returns:

Name	Type	Description
EarthModel	EarthModel	Gravity-model constants and spherical-harmonic coefficient metadata for this variant.

get_name()

Returns the string name of this gravity model.

Returns:

Name	Type	Description
str	str	One of "EGM96", "EGM2008", "WGS84".

get_value()

Returns the integer code for this gravity model.

Returns:

Name	Type	Description
int	int	EGM96=0, EGM2008=1, WGS84=2.

EphemerisSource

Source algorithm used to compute a planetary or lunar ephemeris.

Controls whether celestial-body positions are evaluated with an internal analytical model or tabulated data from the JPL Horizons service.

Attributes:

Name	Type	Description
Analytical	EphemerisSource	Internal low-precision analytical model (e.g., Meeus truncated series). Fast and allocation-free; suitable for force-model perturbation computations where sub-arcsecond accuracy is not required.
Horizons	EphemerisSource	Tabulated ephemeris data retrieved from the JPL Horizons web interface. Higher accuracy than the analytical model; requires network access or a locally cached Horizons data file.

__repr__()

Returns EphemerisSource('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this ephemeris source.

Returns:

Name	Type	Description
str	str	One of "Analytical", "Horizons".

get_value()

Returns the integer code for this ephemeris source.

Returns:

Name	Type	Description
int	int	Analytical=0, Horizons=1.

EstimationFilterMode

Operating mode of a self-relaxing sequential estimator.

Reported by AdaptiveOrbitEstimator so callers can track what the filter is doing as it ingests observations.

Attributes:

Name	Type	Description
Nominal	EstimationFilterMode	Accepting observations and tracking normally.
Recovering	EstimationFilterMode	Sustained rejection triggered recovery; the orchestrator is scoring candidate orbits over the rejected span to begin accepting observations again.
Failing	EstimationFilterMode	No single candidate explains the rejected span, so multiple hypotheses are carried until one is confirmed.

__repr__()

Returns EstimationFilterMode('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this filter mode.

Returns:

Name	Type	Description
str	str	One of "Nominal", "Recovering", "Failing".

HBRShape

Hard-body region shape for the 2D probability-of-collision integral.

The encounter-plane integral of the relative-position Gaussian is taken over this region. Because the covariance is rotated to its principal axes before integration, a square domain separates into a product of two 1D normal-CDF differences — closed-form, no quadrature.

Attributes:

Name	Type	Description
Circle	HBRShape	Hard-body disk of radius HBR. The default, and the only shape the earlier Chan series supported.
Square	HBRShape	Axis-aligned square of half-side HBR (side 2·HBR). Matches NASA CARA's Pc2D_Foster 'square' HBR type.
SquareEquivalentArea	HBRShape	Axis-aligned square with the same area as the HBR disk (half-side √π/2·HBR, side √π·HBR). Matches NASA CARA's Pc2D_Foster 'squareEquArea' HBR type.

__repr__()

Returns HBRShape('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this hard-body shape.

Returns:

Name	Type	Description
str	str	One of "Circle", "Square", "SquareEquivalentArea".

IntegratorType

Numerical integration algorithm used by the XP propagator.

All three variants integrate the equations of motion in Cartesian coordinates. Step-size control and suitability differ; see individual variant docs for guidance on when to prefer each.

Attributes:

Name	Type	Description
RungeKutta4	IntegratorType	Classic fixed-step 4th-order Runge-Kutta. Simple and predictable; requires a small step size to match the accuracy of the adaptive variants.
DormandPrince54	IntegratorType	Dormand-Prince 5(4) embedded Runge-Kutta with adaptive step-size control (DOPRI5 / RK45). Good general-purpose choice for smooth force models.
GaussJackson8	IntegratorType	Gauss-Jackson 8th-order Störmer-Cowell predictor-corrector (PEC). One force evaluation per step; validated to mm-level drift over 7-day arcs.

__repr__()

Returns IntegratorType('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this integrator type.

Returns:

Name	Type	Description
str	str	One of "RungeKutta4", "DormandPrince54", "GaussJackson8".

get_value()

Returns the integer code for this integrator type.

Returns:

Name	Type	Description
int	int	RungeKutta4=0, DormandPrince54=1, GaussJackson8=2.

InterpolationMethod

Ephemeris interpolation method recorded in a CCSDS OEM segment.

Carried as the INTERPOLATION keyword. keplime's own Ephemeris auto-selects cubic/quintic Hermite from whether states carry acceleration, so on ingest this is informational; on emit keplime writes Hermite.

Attributes:

Name	Type	Description
Linear	InterpolationMethod	Linear interpolation.
Lagrange	InterpolationMethod	Lagrange polynomial interpolation.
Hermite	InterpolationMethod	Hermite interpolation; keplime's emit default.

__repr__()

Returns InterpolationMethod('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the CCSDS string token of this method.

Returns:

Name	Type	Description
str	str	One of "LINEAR", "LAGRANGE", "HERMITE".

KeplerianType

Orbit element type describing the averaging theory or osculating convention.

The type determines the compatible propagator and gravitational parameter (μ). GP types use WGS72 constants with SGP4/SDP4; XP and osculating types use EGM96 constants with the numerical XP integrator.

Attributes:

Name	Type	Description
MeanKozaiGP	KeplerianType	Mean elements, Kozai SGP4/SDP4 secular theory, WGS72 μ. Integer code 0.
MeanBrouwerGP	KeplerianType	Mean elements, Brouwer general-perturbation theory, WGS72 μ. Integer code 2.
MeanKozaiPPT3	KeplerianType	Mean elements, PPT3 analytic theory (Kozai mean motion, lunisolar and resonance perturbations), WGS72 μ. Integer code 3. Carried by TLE ephemeris type 3.
MeanBrouwerXP	KeplerianType	Mean elements, Brouwer extended-perturbation (XP) theory, EGM96 μ. Integer code 4.
Osculating	KeplerianType	Osculating (instantaneous) Keplerian elements, EGM96 μ. Integer code 6.

__repr__()

Returns KeplerianType('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this Keplerian type.

Returns:

Name	Type	Description
str	str	One of "MeanKozaiGP", "MeanBrouwerGP",
	str	"MeanKozaiPPT3", "MeanBrouwerXP", "Osculating".

get_value()

Returns the integer code for this Keplerian type.

Returns:

Name	Type	Description
int	int	MeanKozaiGP=0, MeanBrouwerGP=2, MeanKozaiPPT3=3,
	int	MeanBrouwerXP=4, Osculating=6.

MeanElementTheory

Mean-element theory tag for a CCSDS Orbit Mean-Elements Message (OMM).

Identifies the analytic theory the OMM mean elements are expressed for, carried as the MEAN_ELEMENT_THEORY keyword. The variant selects which optional TLE force terms are meaningful — BSTAR for SGP4 versus BTERM/AGOM for SGP4-XP.

Attributes:

Name	Type	Description
SGP4	MeanElementTheory	Classical SGP4 (NORAD General Perturbations); TLE ephemeris type 0/2.
SGP4XP	MeanElementTheory	SGP4-XP extended theory; TLE ephemeris type 4. Its string name is "SGP4-XP".

__repr__()

Returns MeanElementTheory('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the CCSDS string token of this theory.

Returns:

Name	Type	Description
str	str	"SGP4" or "SGP4-XP".

NutationModel

IAU nutation model used in the Earth orientation / precession-nutation computation.

Currently only the IAU 2000B truncated model is supported. The full IAU 2000A series is selected implicitly when PerformancePriority.Precision is chosen.

Attributes:

Name	Type	Description
IAU2000B	NutationModel	IAU 2000B truncated nutation series (77 luni-solar terms + 1 planetary term). Agrees with IAU 2000A to within ~1 mas over the typical operational epoch range.

__repr__()

Returns NutationModel('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this nutation model.

Returns:

Name	Type	Description
str	str	"IAU2000B".

OrbitDeterminationQuality

Quality classification for an orbit determination solution.

Higher quality indicates more observations, better residuals, and smaller position uncertainty. Numeric values: Low=0, Medium=1, High=2.

Attributes:

Name	Type	Description
High	OrbitDeterminationQuality	Well-determined orbit; low position uncertainty, many observations.
Medium	OrbitDeterminationQuality	Moderately constrained orbit; acceptable for routine tasking.
Low	OrbitDeterminationQuality	Poorly constrained orbit; large uncertainty, use with caution.

__repr__()

Returns OrbitDeterminationQuality('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this quality level.

Returns:

Name	Type	Description
str	str	One of "High", "Medium", "Low".

get_value()

Returns the integer code for this quality level.

Returns:

Name	Type	Description
int	int	Low=0, Medium=1, High=2.

PcSampleMotion

Relative-motion model used by the Monte Carlo probability-of-collision estimator.

Attributes:

Name	Type	Description
LinearRelative	PcSampleMotion	Rectilinear relative motion at the mean relative velocity; samples the relative position only and scores a closed-form minimum miss distance. The apples-to-apples cross-check of the analytic Foster Pc. Default.
TwoBody	PcSampleMotion	Two-body propagation of each sampled 6D state across the encounter window. The only mode that samples velocity covariance; quantifies encounter-curvature error in the linear model.

__repr__()

Returns PcSampleMotion('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this motion model.

Returns:

Name	Type	Description
str	str	One of "LinearRelative", "TwoBody".

PerformancePriority

Performance/accuracy priority for frame transforms and force models.

Used to select between full-precision, balanced, and fast model variants (e.g. IAU 2000A vs. IAU 2000B nutation series).

Attributes:

Name	Type	Description
Precision	PerformancePriority	Full IAU 2000A nutation/precession series; highest accuracy, highest CPU cost.
Balanced	PerformancePriority	Hybrid profile with IAU 2000B nutation and moderate-fidelity frame transforms.
Speed	PerformancePriority	IAU 2000B nutation with IAU 2006 precession adjustments; fastest, lowest accuracy.

__repr__()

Returns PerformancePriority('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this performance priority.

Returns:

Name	Type	Description
str	str	One of "Precision", "Balanced", "Speed".

ReferenceFrame

Cartesian reference frame for position and velocity vectors.

Frames are divided into inertial (ECI), Earth-fixed (ECF), and relative categories. The frames module provides transforms between all listed frames.

Attributes:

Name	Type	Description
TEME	ReferenceFrame	True Equator, Mean Equinox – native SGP4/SDP4 output frame.
ITRF	ReferenceFrame	International Terrestrial Reference Frame; Earth-fixed, includes polar motion.
PEF	ReferenceFrame	Pseudo-Earth-Fixed; Earth-fixed without polar-motion correction.
J2000	ReferenceFrame	J2000 mean-equatorial inertial frame (ECI / EME2000).
GCRS	ReferenceFrame	Geocentric Celestial Reference System; ECI frame aligned to IAU 2000A.
RIC	ReferenceFrame	Radial-In-track-Cross-track local-vertical/local-horizontal relative frame.

__repr__()

Returns ReferenceFrame('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this reference frame.

Returns:

Name	Type	Description
str	str	One of "TEME", "ITRF", "PEF", "J2000",
	str	"GCRS", "RIC".

get_value()

Returns the integer code for this reference frame.

Returns:

Name	Type	Description
int	int	TEME=0, ITRF=1, PEF=2, J2000=3,
	int	GCRS=4, RIC=5.

RelativeFrame

Describes whether a relative state is expressed in a rotating or inertial frame.

Used when reporting proximity or close-approach states between two objects.

Attributes:

Name	Type	Description
Rotating	RelativeFrame	RIC (Radial-In-track-Cross-track) rotating frame; co-rotates with the reference orbit.
Inertial	RelativeFrame	Position and velocity difference expressed in the inertial ECI frame.

__repr__()

Returns RelativeFrame('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this relative frame.

Returns:

Name	Type	Description
str	str	One of "Rotating", "Inertial".

TimeSystem

Time reference system for epoch values.

Every ModifiedJulianDate carries an explicit TimeSystem tag. Use to_system to convert between systems.

The conversion graph supported by the library is:

UTC ↔ TAI ↔ TT ↔ TDB
UTC ↔ UT1
GPS ↔ TAI

Attributes:

Name	Type	Description
UTC	TimeSystem	Coordinated Universal Time; the standard civil timescale with leap seconds.
TAI	TimeSystem	International Atomic Time; continuous, no leap seconds. TAI = UTC + (current leap-second offset).
TT	TimeSystem	Terrestrial Time; TT = TAI + 32.184 s, used in modern ephemerides.
UT1	TimeSystem	Universal Time corrected for Earth rotation; offset from UTC provided by IERS Finals tables (|UT1−UTC| < 0.9 s).
TDB	TimeSystem	Barycentric Dynamical Time; differs from TT by up to ~1.7 ms due to relativistic periodic terms.
GPS	TimeSystem	Global Positioning System time; continuous atomic timescale used by GNSS. GPS = TAI − 19 s; epoch 1980-01-06T00:00:00 UTC. No leap seconds.

__repr__()

Returns TimeSystem('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this time system.

Returns:

Name	Type	Description
str	str	One of "UTC", "TAI", "TT", "UT1", "TDB", "GPS".

get_value()

Returns the integer code for this time system.

Returns:

Name	Type	Description
int	int	UTC=0, TAI=1, TT=2, UT1=3, TDB=4, GPS=5.

TrackletFormation

Strategy for grouping raw observations into tracklets.

Construct via the variant-specific classmethods rather than __init__: adaptive_motion_continuity, fixed_thresholds, two_pass, and dbscan. default returns the balanced AdaptiveMotionContinuity default.

__repr__()

Returns a constructor-style call carrying the variant parameters, e.g. TrackletFormation.adaptive_motion_continuity(k_sigma_gate=…, max_gap_seconds=…).

__str__()

Returns the bare variant name (same string as get_name).

adaptive_motion_continuity(k_sigma_gate, max_gap_seconds) classmethod

Greedy per-sensor extension driven by a running angular-rate fit.

Parameters:

Name	Type	Description	Default
k_sigma_gate	float	Gate width on the running angular-rate prediction [dimensionless; >= 0].	required
max_gap_seconds	float	Hard maximum time gap between adjacent observations [s; > 0].	required

Returns:

Name	Type	Description
TrackletFormation	TrackletFormation	The configured strategy.

dbscan(eps_seconds, eps_arcsec, min_samples) classmethod

DBSCAN clustering on (t, α, δ) with a modality-aware metric.

Parameters:

Name	Type	Description	Default
eps_seconds	float	Time-axis neighbourhood radius [s; > 0].	required
eps_arcsec	float	Angular-axis neighbourhood radius [arcsec; > 0].	required
min_samples	int	Minimum cluster size [count; >= 2].	required

Returns:

Name	Type	Description
TrackletFormation	TrackletFormation	The configured strategy.

default() classmethod

Returns the balanced default (AdaptiveMotionContinuity with k_sigma_gate=3.0 and max_gap_seconds=300.0).

Returns:

Name	Type	Description
TrackletFormation	TrackletFormation	The default strategy.

fixed_thresholds(max_gap_seconds, max_angular_jump_arcsec) classmethod

Two fixed thresholds on time gap and great-circle angular jump.

Parameters:

Name	Type	Description	Default
max_gap_seconds	float	Hard maximum time gap [s; > 0].	required
max_angular_jump_arcsec	float	Hard maximum great-circle angular separation between adjacent observations [arcsec; > 0].	required

Returns:

Name	Type	Description
TrackletFormation	TrackletFormation	The configured strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of "AdaptiveMotionContinuity", "FixedThresholds",
	str	"TwoPass", "DBSCAN".

two_pass(coarse_gap_seconds, motion_k_sigma_gate) classmethod

Two-pass: coarse time-gap split, then motion-continuity split.

Parameters:

Name	Type	Description	Default
coarse_gap_seconds	float	Coarse time-gap threshold for the first pass [s; > 0].	required
motion_k_sigma_gate	float	Motion-continuity gate used inside each first-pass bucket [dimensionless; >= 0].	required

Returns:

Name	Type	Description
TrackletFormation	TrackletFormation	The configured strategy.

TrackletModality

Measurement modality common to every observation in a Tracklet.

Drives downstream IOD and admissible-region dispatch — angles-only tracklets need the admissible-region machinery, while radar tracklets carry enough information for direct algebraic IOD.

Attributes:

Name	Type	Description
OpticalAngles	TrackletModality	Optical angles-only (right ascension and declination). Range and range-rate are unobserved. Drives the admissible-region path.
Radar	TrackletModality	Radar observations carrying range, range-rate, and angles. Provides enough information for direct algebraic initial orbit determination.
Bistatic	TrackletModality	Bistatic / passive-RF observations carrying time-difference-of-arrival (TDOA) and optionally frequency-difference-of-arrival (FDOA) between two sensors.
AngleRates	TrackletModality	Optical angles-only with reported angular rates. Higher information content than OpticalAngles alone — angle rates allow Laplace's method to seed IOD from a single epoch.

__repr__()

Returns TrackletModality('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this tracklet modality.

Returns:

Name	Type	Description
str	str	One of "OpticalAngles", "Radar", "Bistatic", "AngleRates".

get_value()

Returns the integer code for this tracklet modality.

Returns:

Name	Type	Description
int	int	OpticalAngles=0, Radar=1, Bistatic=2, AngleRates=3.

UCTExpansionMethod

Strategy for the expansion loop that gates unassigned observations against each refined candidate.

Construct via the variant-specific classmethods rather than __init__: mahalanobis_gate and ar_respawn. default returns MahalanobisGate { gate_chi2=9.0 }.

__repr__()

Returns a constructor-style call carrying the variant parameters, e.g. UCTExpansionMethod.mahalanobis_gate(gate_chi2=…).

__str__()

Returns the bare variant name (same string as get_name).

ar_respawn(gate_chi2, position_sigma_km, velocity_sigma_km_per_s) classmethod

AR-respawn fallback when Mahalanobis stalls.

Parameters:

Name	Type	Description	Default
gate_chi2	float	Chi-squared gate used for the Mahalanobis pass that follows the respawn [dimensionless; > 0].	required
position_sigma_km	float	Position-axis 1-σ used to size the respawned AR [km; > 0].	required
velocity_sigma_km_per_s	float	Velocity-axis 1-σ used to size the respawned AR [km/s; > 0].	required

Returns:

Name	Type	Description
UCTExpansionMethod	UCTExpansionMethod	The configured strategy.

default() classmethod

Returns the balanced default (MahalanobisGate with gate_chi2=9.0).

Returns:

Name	Type	Description
UCTExpansionMethod	UCTExpansionMethod	The default strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of "MahalanobisGate", "ARRespawn".

mahalanobis_gate(gate_chi2) classmethod

Mahalanobis-distance gate on unassigned observations.

Parameters:

Name	Type	Description	Default
gate_chi2	float	Chi-squared gate threshold [dimensionless; > 0]. Smaller is more conservative. Typical value 9.0 (3-sigma).	required

Returns:

Name	Type	Description
UCTExpansionMethod	UCTExpansionMethod	The configured strategy.

UCTIODMethod

Initial-orbit-determination dispatch for the UCT pipeline.

Class-level constants select the requested IOD algorithm. Explicit multi-tracklet methods still generate admissible-region particles during single-tracklet hypothesis generation, then run the selected method once correlation supplies three compatible tracklets.

Attributes:

Name	Type	Description
Auto	UCTIODMethod	Automatic dispatch based on observation modality.
Gauss	UCTIODMethod	Classical Gauss angles-only IOD.
Lambert	UCTIODMethod	Lambert two-point boundary-value solve.
HerrickGibbs	UCTIODMethod	Herrick-Gibbs velocity estimate.
Laplace	UCTIODMethod	Laplace angles-only IOD.
DoubleR	UCTIODMethod	Double-R angles-only IOD.
Gooding	UCTIODMethod	Gooding angles-only IOD.
MultiRevGauss	UCTIODMethod	Multi-revolution Gauss dispatch.
KarimiMortari	UCTIODMethod	Karimi-Mortari mixed-modality IOD.
ARSeed	UCTIODMethod	Admissible-region seeded refinement.

__repr__()

Returns UCTIODMethod.….

__str__()

Returns the bare variant name (same string as get_name).

default() classmethod

Returns the balanced default (Auto).

Returns:

Name	Type	Description
UCTIODMethod	UCTIODMethod	The default strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of the class-level constant names.

UCTObservability

Observability status of an uncorrelated track (UCT) against a sensor pass.

Numeric values: Confirmed=0, Possible=1, Unavailable=2.

Attributes:

Name	Type	Description
Confirmed	UCTObservability	Object is geometrically confirmed within the sensor's field of view.
Possible	UCTObservability	Object may be observable depending on attitude, obscuration, or sensitivity.
Unavailable	UCTObservability	Object is not observable (geometry, Earth shadow, or out-of-range).

__repr__()

Returns UCTObservability('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this observability status.

Returns:

Name	Type	Description
str	str	One of "Confirmed", "Possible", "Unavailable".

get_value()

Returns the integer code for this observability status.

Returns:

Name	Type	Description
int	int	Confirmed=0, Possible=1, Unavailable=2.

UCTRefinementMethod

Estimator used to refine each candidate after IOD.

Class-level constants for each variant. default returns BLS.

Attributes:

Name	Type	Description
BLS	UCTRefinementMethod	Iterated Gauss-Newton batch least squares (default).
UKF	UCTRefinementMethod	Unscented Kalman filter.
EKF	UCTRefinementMethod	Extended Kalman filter.

__repr__()

Returns UCTRefinementMethod.….

__str__()

Returns the bare variant name (same string as get_name).

default() classmethod

Returns the balanced default (BLS).

Returns:

Name	Type	Description
UCTRefinementMethod	UCTRefinementMethod	The default strategy.

get_name()

Returns the variant name.

Returns:

Name	Type	Description
str	str	One of "BLS", "UKF", "EKF".

UCTValidity

Classifier for the physical validity of an uncorrelated track (UCT).

Numeric values: LikelyReal=0, PossibleCrossTag=1, PossibleManeuver=2, Inconclusive=3.

Attributes:

Name	Type	Description
LikelyReal	UCTValidity	Track residuals are consistent with a real, stable object.
PossibleCrossTag	UCTValidity	Track may result from a cross-tag (misassociation) between two objects.
PossibleManeuver	UCTValidity	Track exhibits dynamics consistent with a manoeuvre or unusual perturbation.
Inconclusive	UCTValidity	Validity cannot be determined from available data.

__repr__()

Returns UCTValidity('…').

__str__()

Returns the bare variant name (same string as get_name).

get_name()

Returns the string name of this validity classification.

Returns:

Name	Type	Description
str	str	One of "LikelyReal", "PossibleCrossTag",
	str	"PossibleManeuver", "Inconclusive".

get_value()

Returns the integer code for this validity classification.

Returns:

Name	Type	Description
int	int	LikelyReal=0, PossibleCrossTag=1,
	int	PossibleManeuver=2, Inconclusive=3.