| Name | angap JSON |
| Version |
0.1
JSON |
| download |
| home_page | |
| Summary | Geometric Approach for Analytical Approximations of Satellite Coverage Statistics |
| upload_time | 2023-05-17 01:54:43 |
| maintainer | |
| docs_url | None |
| author | Tim Hackett |
| requires_python | |
| license | MIT |
| keywords |
analytical
coverage
approximations
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
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The analysis and optimization of satellite coverage statistics have been ongoing for several decades. Designing an orbit or a constellation of orbits to meet specific coverage statistics (such as the mean pass duration, mean passes per day, and maximum gap time) can help maximize coverage time and meet mission goals for ground-based assets.
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