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Merge pull request #37 from thkruz/claude/conjunction-assessment-workflow-013nkXNDCBzpdeJG9z7Y7N2b
feat: add high accuracy conjunction assessment workflow
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‎examples/conjunction-assessment-example.ts‎

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/**
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* @file Conjunction Assessment Example
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* @description Demonstrates high accuracy conjunction assessment using
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* historical TLE accuracy and covariance propagation.
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*
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* This example shows how to:
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* 1. Set up a conjunction assessment between two space objects
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* 2. Use high-fidelity propagators for improved accuracy
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* 3. Propagate covariance matrices based on TLE quality
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* 4. Calculate probability of collision
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*
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* @author Theodore Kruczek
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* @license AGPL-3.0-or-later
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* @copyright (c) 2025 Kruczek Labs LLC
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*/
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import {
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ConjunctionAssessment,
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EpochUTC,
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ForceModel,
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Kilometers,
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Tle,
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StateCovariance,
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CovarianceFrame,
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} from '../src/main';
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// Example 1: Basic Conjunction Assessment using TLEs
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function basicConjunctionAssessment() {
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console.log('=== Example 1: Basic Conjunction Assessment ===\n');
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// Sample TLE data for two satellites in close proximity
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const primaryTle = new Tle(
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'1 25544U 98067A 25019.50000000 .00016717 00000-0 10270-3 0 9005',
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'2 25544 51.6400 339.8000 0002571 90.5000 269.6000 15.50000000000000',
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);
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const secondaryTle = new Tle(
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'1 44691U 19074A 25019.50000000 .00016500 00000-0 10200-3 0 9006',
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'2 44691 51.6450 339.8050 0002600 90.5050 269.6050 15.50005000000000',
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);
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// Create conjunction assessment with object radii
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const assessment = new ConjunctionAssessment(
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{
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name: 'ISS (Zarya)',
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tle: primaryTle,
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radius: 0.05 as Kilometers, // 50 meters
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},
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{
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name: 'Secondary Object',
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tle: secondaryTle,
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radius: 0.01 as Kilometers, // 10 meters
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},
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);
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// Define search window (6 hours)
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const startTime = EpochUTC.fromDateTimeString('2025-01-19T12:00:00.000Z');
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const endTime = EpochUTC.fromDateTimeString('2025-01-19T18:00:00.000Z');
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// Perform conjunction assessment
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const event = assessment.assess({
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startTime,
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endTime,
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});
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// Display results
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console.log(event.toString());
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console.log(`\nHigh Risk: ${event.isHighRisk(1.0 as Kilometers)}`);
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}
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// Example 2: High-Fidelity Propagation with Covariance
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function highFidelityConjunctionAssessment() {
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console.log('\n=== Example 2: High-Fidelity Assessment with Covariance ===\n');
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const primaryTle = new Tle(
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'1 25544U 98067A 25019.50000000 .00016717 00000-0 10270-3 0 9005',
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'2 25544 51.6400 339.8000 0002571 90.5000 269.6000 15.50000000000000',
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);
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const secondaryTle = new Tle(
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'1 44691U 19074A 25019.50000000 .00016500 00000-0 10200-3 0 9006',
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'2 44691 51.6450 339.8050 0002600 90.5050 269.6050 15.50005000000000',
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);
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const assessment = new ConjunctionAssessment(
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{
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name: 'ISS (Zarya)',
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tle: primaryTle,
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radius: 0.05 as Kilometers,
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},
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{
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name: 'Secondary Object',
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tle: secondaryTle,
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radius: 0.01 as Kilometers,
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},
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);
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const startTime = EpochUTC.fromDateTimeString('2025-01-19T12:00:00.000Z');
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const endTime = EpochUTC.fromDateTimeString('2025-01-19T18:00:00.000Z');
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// Use high-fidelity propagation with force model
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const forceModel = new ForceModel().setGravity(8, 8).setAtmosphericDrag().setSolarRadiationPressure();
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const event = assessment.assess({
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startTime,
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endTime,
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useHighFidelity: true,
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forceModel,
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propagateCovariance: true, // Propagate TLE-based covariances
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});
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console.log(event.toString());
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if (event.probabilityOfCollision !== undefined) {
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console.log(`\nProbability of Collision: ${event.probabilityOfCollision.toExponential(6)}`);
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}
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if (event.getMahalanobisDistance() !== undefined) {
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console.log(`Mahalanobis Distance: ${event.getMahalanobisDistance()!.toFixed(3)} sigma`);
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}
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}
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// Example 3: Custom Covariance Matrices
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function customCovarianceAssessment() {
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console.log('\n=== Example 3: Custom Covariance Matrices ===\n');
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const primaryTle = new Tle(
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'1 25544U 98067A 25019.50000000 .00016717 00000-0 10270-3 0 9005',
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'2 25544 51.6400 339.8000 0002571 90.5000 269.6000 15.50000000000000',
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);
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const secondaryTle = new Tle(
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'1 44691U 19074A 25019.50000000 .00016500 00000-0 10200-3 0 9006',
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'2 44691 51.6450 339.8050 0002600 90.5050 269.6050 15.50005000000000',
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);
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// Define custom covariances (1-sigma values in RIC frame)
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// [radial, intrack, crosstrack, radial_vel, intrack_vel, crosstrack_vel]
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const primaryCovariance = StateCovariance.fromSigmas(
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[
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0.5, // 500 m radial uncertainty
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1.5, // 1.5 km intrack uncertainty
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0.5, // 500 m crosstrack uncertainty
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0.001, // 1 m/s radial velocity uncertainty
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0.003, // 3 m/s intrack velocity uncertainty
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0.001, // 1 m/s crosstrack velocity uncertainty
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],
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CovarianceFrame.RIC,
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);
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const secondaryCovariance = StateCovariance.fromSigmas(
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[0.3, 1.0, 0.3, 0.0005, 0.002, 0.0005],
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CovarianceFrame.RIC,
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);
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const assessment = new ConjunctionAssessment(
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{
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name: 'ISS (Zarya)',
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tle: primaryTle,
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covariance: primaryCovariance,
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radius: 0.05 as Kilometers,
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},
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{
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name: 'Secondary Object',
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tle: secondaryTle,
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covariance: secondaryCovariance,
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radius: 0.01 as Kilometers,
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},
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);
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const startTime = EpochUTC.fromDateTimeString('2025-01-19T12:00:00.000Z');
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const endTime = EpochUTC.fromDateTimeString('2025-01-19T18:00:00.000Z');
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const event = assessment.assess({
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startTime,
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endTime,
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});
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console.log(event.toString());
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}
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// Example 4: Screening Multiple Objects
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function screeningExample() {
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console.log('\n=== Example 4: Multi-Object Screening ===\n');
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const primaryTle = new Tle(
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'1 25544U 98067A 25019.50000000 .00016717 00000-0 10270-3 0 9005',
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'2 25544 51.6400 339.8000 0002571 90.5000 269.6000 15.50000000000000',
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);
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// List of potential conjunction objects
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const secondaryTles = [
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new Tle(
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'1 44691U 19074A 25019.50000000 .00016500 00000-0 10200-3 0 9006',
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'2 44691 51.6450 339.8050 0002600 90.5050 269.6050 15.50005000000000',
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),
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new Tle(
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'1 12345U 81001A 25019.50000000 .00016400 00000-0 10100-3 0 9007',
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'2 12345 51.6500 339.8100 0002650 90.5100 269.6100 15.50010000000000',
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),
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];
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const startTime = EpochUTC.fromDateTimeString('2025-01-19T12:00:00.000Z');
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const endTime = EpochUTC.fromDateTimeString('2025-01-19T18:00:00.000Z');
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const screeningThreshold = 5.0 as Kilometers; // 5 km screening threshold
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const pcThreshold = 1e-6; // Pc > 1e-6 is concerning
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console.log(`Screening ${secondaryTles.length} objects for conjunctions...\n`);
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secondaryTles.forEach((secondaryTle, index) => {
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const assessment = new ConjunctionAssessment(
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{ tle: primaryTle, radius: 0.05 as Kilometers },
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{ tle: secondaryTle, radius: 0.01 as Kilometers },
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);
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const event = assessment.assess({
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startTime,
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endTime,
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useHighFidelity: true,
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propagateCovariance: true,
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});
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if (event.missDistance < screeningThreshold) {
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console.log(`Object ${index + 1}: CLOSE APPROACH DETECTED`);
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console.log(` TCA: ${event.tca.toISOString()}`);
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console.log(` Miss Distance: ${event.missDistance.toFixed(3)} km`);
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if (event.probabilityOfCollision !== undefined && event.probabilityOfCollision > pcThreshold) {
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console.log(` Pc: ${event.probabilityOfCollision.toExponential(3)} [HIGH RISK]`);
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} else if (event.probabilityOfCollision !== undefined) {
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console.log(` Pc: ${event.probabilityOfCollision.toExponential(3)}`);
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}
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console.log();
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}
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});
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}
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// Run all examples
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if (require.main === module) {
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basicConjunctionAssessment();
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highFidelityConjunctionAssessment();
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customCovarianceAssessment();
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screeningExample();
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console.log('\n=== All Examples Complete ===');
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}

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