Space Data Actionability Metrics for SSA AGI User's Conference October 2005 Space Data Actionability Metrics for SSA Center for Space Standards and Innovation Dan Oltrogge, T.S. Kelso, S. Alfano, D. Vallado & J. Griesbach 29 June 2011 www.agi.com

Contents Review Improvement Opportunities for Space Positional Knowledge Variety of SSA metrics for RFI, CA Data Source Accuracy Actionability Metrics for Data Suitability of Data/Pairings for SSA Conclusions

Opportunities for More Effective Satellite Position Estimation Have challenges in our ability to estimate satellite position These issues affect accuracy of predicted satellite position vs time Want to explore SSA impacts of Improvement Opp #2, #3, #4… Opportunity: Affected Data Source Affected Orbit(s) Opp #1: Identifying satellites correctly – mitigating cross tagging NCT GEO, LEO Opp #2: Tracking satellites better, particularly through maneuvers Opp #3: Improving orbit estimation and propagation to account for uncertainty in drag due to changes in the atmosphere (space weather, satellite attitude) O/O + NCT LEO Opp #4: Making sensor tasking more effective (tasking and measurement duration/intervals) Opp #5: Making analysis practices interoperable and more consistent

Space Positional Data Sources AGI User's Conference October 2005 Space Positional Data Sources Data Source Generic Nomenclature: NCT = Non-Cooperative Tracker Examples include SSN/JSpOC, ISON, ESA NCT sensors don’t have to interrogate or “cooperate” with satellite to determine position O/O = Owner/Operator e.g., SDA, indiv operators, ESA, NASA Data Source Notional Accuracy: Source Sensor Debris Live Sats NCT Radar Optical O/O Active Ranging www.agi.com

Variety of SSA metrics for CA, RFI For CA, many metrics to evaluate collision risk: Miss distance at TCA Mahalanobis distance at TCA for both straight and bent ellipsoids Max Probability (linearized relative motion) Analytical True Probability (linearized relative motion) Numerical True Probability (linearized relative motion) Analytical True Probability (nonlinear relative motion) Numerical True Probability (nonlinear relative motion) Also a variety of weighted, combined metrics: NASA has had success with “F-factor” (Newman, Frigm, et al) Objective of F-factor is to prioritize conjunctions and alleviate operators from having to sift through long lists of potential conjunctions that nothing can be done for RFI is also an SSA issue… Actionability & sensitivity of RFI input data complex, but clearly significant

RFI Event Detection Can define RFI as:

Error Growth and Unmodeled Forces Nominal predicted trajectory drifts away from actual path if unmodeled perturbations or maneuvers exist Error growth may or may not incorporate unmodeled forces Iridium/Cosmos impact caused by covariance not encompassing maneuver

Tasking Resonance = Similar Degradation Optical tracking relies on lighting conditions to illuminate space object during darkness at optical sensor (> astronomical twilight) Can lead to under-sampling conditions with observations collected only in evening and early morning Sensor Position Error (km)

Orbit Sol’ns at Unknown Maneuvers Tracking across maneuver(s) Degrades orbit solution accuracy Low thrust, long duration burns common at GEO But what portion of objects are operational? For GEO, turns out to be quite high; for GEO ±300km: 873 active sats out of 1523 (nearly 60%)

SSA Data Actionability Analysis Insight gleaned by analyzing test cases where SSA threat occurs For RFI, can develop test cases of RFI and examine impact of degrading orbit solutions, frequencies, TDOA and FDOA measurement uncertainty Demonstrated yesterday For CA, can develop collision test cases and examine impact of degraded orbit solutions, collision geometries, erroneous object sizes, etc For purposes of study, adopted following SSA maneuver action thresholds: One-in-1,000,000 triggers a warning (i.e. keep an eye on this) One-in-100,000 triggers a meeting to discuss/plan maneuver options One-in-10,000 causes some executive-level decision maker to give a GO or NO-GO maneuver call

Already Presented This Approach For RFI 10° Longitude Separation TLE-vs-TLE TLE-vs-SDA SDA-vs-SDA

Collision Probability Sensitivity Study Conducting literature and peer survey to assess ‘representative’ levels of accuracy for different data sources Preliminary results excerpted from upcoming AAS paper research Simulated direct collision (zero miss distance) Defined “encounter angle” & characterized maximum collision probability for each combination of data types

Peer-Based Error Metrics for GEO Examined all combinations of GEO data sources VNC error metrics estimated by research aggregation and peer review

Actionability With Unknown Maneuvers Tracking across maneuver(s) Degrades orbit solution accuracy Low thrust, long duration burns common at GEO

GEO “Actionability” vs Data, Encounter Angle Preliminary * Excerpt from Upcoming CSSI Tech Paper

Peer-Based Error Metrics for LEO

Opp #3: Improving drag modeling in orbit estimation and propagation (cont.)

LEO “Actionability” vs Data, Encounter Angle Preliminary * Excerpt from Upcoming CSSI Tech Paper

Conclusions Data Fusion critical for actionable SSA product No data source can “do it all” SDA (Owner/Operator) data only for active satellites NCT data products affected by: Cross-Tags Fitting orbits thru unknown maneuvers Sensor observation timing biases Potential lack of priority for your mission