Researchers have developed and evaluated three consensus-based distributed filtering strategies for angles-only spacecraft navigation in cislunar space. These methods aim to estimate a target spacecraft's state using only line-of-sight measurements from multiple observer spacecraft, addressing challenges like communication constraints and single-point failures inherent in centralized systems. The approaches, including the Distributed Extended Kalman Filter, Information-Weighted Consensus Filter, and Kalman Consensus Filter, were compared against a centralized Extended Kalman Filter and independent local filters. Numerical simulations demonstrated that the distributed methods significantly enhance estimation accuracy compared to independent filters, with sensitivity analyses characterizing their robustness to limited consensus iterations and prior misalignment. AI
IMPACT These distributed filtering techniques could improve the autonomy and reliability of spacecraft navigation systems, particularly in challenging environments like cislunar space.
RANK_REASON The cluster contains an academic paper detailing new methods and simulation results. [lever_c_demoted from research: ic=1 ai=0.4]
Read on arXiv cs.MA (Multiagent) →
- arXiv
- cislunar space
- extended Kalman filter
- Giovanni Romagnoli
- Information-Weighted Consensus Filter
- Kalman Consensus Filter
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