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Unified Orbit-Attitude Estimation and Sensor Tasking Framework for Autonomous Cislunar Space Domain Awareness Using Multiplicative Unscented Kalman Filter

Smriti Nandan Paul, Siwei Fan

Abstract

The cislunar regime departs from near-Earth orbital behavior through strongly non-linear, non-Keplerian dynamics, which adversely affect the accuracy of uncertainty propagation and state estimation. Additional challenges arise from long-range observation requirements, restrictive sensor-target geometry and illumination conditions, the need to monitor an expansive cislunar volume, and the large design space associated with space/ground-based sensor placement. In response to these challenges, this work introduces an advanced framework for cislunar space domain awareness (SDA) encompassing two key tasks: (1) observer architecture optimization based on a realistic cost formulation that captures key performance trade-offs, solved using the Tree of Parzen Estimators algorithm, and (2) leveraging the resulting observer architecture, a mutual information-driven sensor tasking optimization is performed at discrete tasking intervals, while orbital and attitude state estimation is carried out at a finer temporal resolution between successive tasking updates using an error-state multiplicative unscented Kalman filter. Numerical simulations demonstrate that our approach in Task 1 yields observer architectures that achieve significantly lower values of the proposed cost function than baseline random-search solutions, while using fewer sensors. Task 2 results show that translational state estimation remains satisfactory over a wide range of target-to-observer count ratios, whereas attitude estimation is significantly more sensitive to target-to-observer ratios and tasking intervals, with increased rotational-state divergence observed for high target counts and infrequent tasking updates. These results highlight important trade-offs between sensing resources, tasking cadence, and achievable state estimation performance that influence the scalability of autonomous cislunar SDA.

Unified Orbit-Attitude Estimation and Sensor Tasking Framework for Autonomous Cislunar Space Domain Awareness Using Multiplicative Unscented Kalman Filter

Abstract

The cislunar regime departs from near-Earth orbital behavior through strongly non-linear, non-Keplerian dynamics, which adversely affect the accuracy of uncertainty propagation and state estimation. Additional challenges arise from long-range observation requirements, restrictive sensor-target geometry and illumination conditions, the need to monitor an expansive cislunar volume, and the large design space associated with space/ground-based sensor placement. In response to these challenges, this work introduces an advanced framework for cislunar space domain awareness (SDA) encompassing two key tasks: (1) observer architecture optimization based on a realistic cost formulation that captures key performance trade-offs, solved using the Tree of Parzen Estimators algorithm, and (2) leveraging the resulting observer architecture, a mutual information-driven sensor tasking optimization is performed at discrete tasking intervals, while orbital and attitude state estimation is carried out at a finer temporal resolution between successive tasking updates using an error-state multiplicative unscented Kalman filter. Numerical simulations demonstrate that our approach in Task 1 yields observer architectures that achieve significantly lower values of the proposed cost function than baseline random-search solutions, while using fewer sensors. Task 2 results show that translational state estimation remains satisfactory over a wide range of target-to-observer count ratios, whereas attitude estimation is significantly more sensitive to target-to-observer ratios and tasking intervals, with increased rotational-state divergence observed for high target counts and infrequent tasking updates. These results highlight important trade-offs between sensing resources, tasking cadence, and achievable state estimation performance that influence the scalability of autonomous cislunar SDA.
Paper Structure (14 sections, 33 equations, 8 figures, 3 tables)

This paper contains 14 sections, 33 equations, 8 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Modeling and Estimation Background
  3. CR3BP Orbital Dynamics
  4. Optical Brightness Modeling
  5. Analytical Brightness Models
  6. Error-State Multiplicative Unscented Kalman Filter
  7. Observer Architecture Optimization Framework (Task 1)
  8. Integrated Sensor Tasking and State Estimation (Task 2)
  9. Results and Discussions
  10. Architecture Optimization (Task 1) Results
  11. Sensor Tasking and Estimation (Task 2) Results
  12. Sensor Tasking-Estimation Performance: Varying the Number of Targets of Interest
  13. Sensor Tasking-Estimation Performance: Varying the Time Between Tasking Steps
  14. Conclusion

Figures (8)

  • Figure 1: Reflection Geometry for a Representative Surface Facet. (quadrilateral facet shown for illustration purpose, triangular facet is used.)
  • Figure 2: Candidate Observer Orbit Set Consisting of 302 Periodic Trajectories Drawn from 13 Earth-Moon Orbit Families, Shown Together with Fixed Targets in the Rotating Frame (2000 Points).
  • Figure 3: Observer Orbits Selected by the TPE-Based Optimizer for (a) Sparse-Opt (Scenario A), (b) Moderate-Opt (Scenario B), and (c) Dense-Opt (Scenario C).
  • Figure 4: Observer Orbits Selected by the Random Search-Based Optimizer for (a) Sparse-Opt (Scenario A), (b) Moderate-Opt (Scenario B), and (c) Dense-Opt (Scenario C).
  • Figure 5: Scenario A-Based Estimation Performance for Different Target Counts from the Dual Sensor Tasking-Estimation Framework. (a), (b) Show the Fraction of Time Estimation Error is Within $3\sigma$ Bounds. (c), (d) Show Component-Wise ANEES. (e), (f) Show RMSE Values.
  • ...and 3 more figures