Cataloging with an Upgraded Space Surveillance Fence

Transcription

1 Cataloging with an Upgraded Space Surveillance Fence Felix Hoots, Geoff Pierce, Lester Ford AT&T Hugh Hadley Syracuse Research Integrated solutions from a trusted source

2 Fence Provides Robust, Uncued Surveillance Space Surveillance Fence Built in 1958 Great circle inclined 33 o 3 VHF transmitters 6 receivers Provides 175,000 bi-static observations per day Direction cosine data Remainder of worldwide Space Surveillance Network provides another 100,000 observations per day Mostly range, azimuth, elevation 2

3 Fence Nearing End of Maintainability Higher frequency upgrade being planned S band will detect objects as small as 2 cm Current fence has no tracking capability simple detection of fence penetration Will detect as many as 100,000 new objects New fence must have initial orbit estimation capability Simulation of current fence has been extended to assess catalog creation challenges and performance This paper reports A proposed upgraded fence design Initial observation correlation and orbit creation Dynamic observation association algorithm Catalog creation performance 3

4 Dual Fence Design Enables Orbit Estimation Dual Fence in eastern US 6 O tilt of second fence One transmitter and two receivers Measures direction cosines and bistatic range rate Detection at dual fence creates challenges Correlation of detections between two fences Short arc orbit prediction uncertainty View from Atlantic Ocean looking West 4

5 Dual Fence Observation Correlation Initial detection by two receivers at first fence gives a position and time Bi-static range rate gives two components of velocity Assuming circular orbit gives third component of velocity First fence position and velocity used to predict second fence crossing Consider all second fence observations near this predicted point Best fit orbit using first fence ob and second fence candidate ob Bi-static range rates at fences will discriminate to select correct second fence observation for correlation 5

6 Pulling the catalog up by its bootstraps... Two properly correlated observations yield an initial element set and covariance Predict location and uncertainty at the next fence crossing generally one revolution later Use both the prediction uncertainty and the measurement uncertainty at the western fence Observation associate limits are dynamic Depend on initial orbit noise Grow with prediction time Inflated to account for western fence measurement uncertainty Generally, a successful association on the next revolution will lead to a stable and maintainable orbit 6

7 Simulation Includes Radar Operation, Orbit Creation, and Coverage Radar Inputs and Orbit Maintenance Sensitivity NASA Debris Fence Fence Simulation components NASA debris database Truth ephemeris High fidelity radar model Dual fence observation correlation and initial orbit estimation Dynamic observation association Orbit maintenance Section New Object Creation Section Automatic quality Catalog Processing assessment Maintainablity Section Catalog Catalog Propagation Module Position Propagation Module Initial Orbit Evaluate Quality of State Vector State Vectors Geometric Characteristics Fence Crossing Failed Correlation Evaluate Ob Quality and Quantity Update Fence Crossing Table Successful Correlation Correlation & Initial Orbit Module Electronic Characteristics Fence Observation Through a Beam Association Module Refine Orbits (OD) Cluster of all Receiver obs for a given Transmitter hit Dual Fence? Failed Association Observation Buffer Evaluate End to End Successful Association UCT Tagged Single Observations 7

8 # Objects Catalogued Rapidly Creates New Catalog from Scratch Ideal curve shows best possible performance if all obs are perfectly utilized Simulation curve shows actual performance using fence to fence correlation and dynamic association algorithms Days Ideal Simulation 8

9 # False Objects Unsuccessful Orbit Rate is Small Some orbits are created but are not maintainable Noisy initial orbit estimate Association of subsequent obs fails Satellite will have another chance to be cataloged on subsequent fence passage Unsuccessful orbit rate falls off as catalog grows Days 9

10 # UOs Unassociated Observation Rate Diminishes Rapidly Observations of satellites not yet in catalog will not associate Unassociated observation rate falls off rapidly as catalog is created Those remaining after 15 days correspond to uncataloged objects Observations on cataloged satellites generally associate properly Days 10

11 Conclusions Simulation provides tool for realistic assessment of fence cataloging capabilities A new fence with a modest initial orbit estimation capability can autonomously create a catalog from scratch The fence will be able to rapidly add new objects to the catalog With 100,000 new objects to catalog, the process must be automated Must employ smart algorithms Must effectively utilize information (e.g. covariance) Must develop tunable rules for automatic catalog entry Must minimize man in the loop interaction 11