UT Austin's new adaptive model cuts cislunar tracking costs significantly
Efficient uncertainty propagation for the chaotic cislunar region just got a major upgrade—
Researchers Cedric Petion, Benjamin Reifler, and Brandon Jones propose an adaptive multi-fidelity method for uncertainty propagation in cislunar space. The technique dynamically adjusts the included perturbing forces based on position, reducing computation time while maintaining a prescribed modeling accuracy. Integrated into multi-target tracking, it lowers track prediction cost without sacrificing accuracy. Simulated tests show significant computational savings over non-adaptive approaches, crucial for managing the expected growth in cislunar space objects.
- Adaptive method selects perturbing forces based on spacecraft position in cislunar space, reducing computation time
- Integrated into multi-target tracking framework to lower track prediction cost without accuracy loss
- Simulated tests show significant computational savings over non-adaptive approaches for upcoming cislunar missions
Why It Matters
Enables efficient space situational awareness for the rapidly growing number of cislunar objects, critical for collision avoidance and mission safety.