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Manifold Filtering Problem Lockheed Martin Jarett Hailes Jonathan Wiersma Richard VanWeelden July 21, 2003
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Outline Pod problem description Signal / Observation Model SERP Simulation Parameter Details Results IDEX Implementation Sketch of progress towards proof
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Problem Description Pod Sensor Second Sensor
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Signal Description 233 33 : : x h Process WienerD2: t W Stratonovich SDE 3 Dimensional State
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Signal Constraints
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Signal Implementation Stratonovich SDEIto SDE
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Pod Observation Model : basis of plane normal to r r : resting position of pod sensor
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2 4 3 1) Resample Particles 2) Evolve Particles 3) Update Weights given Y k If W(ξ t i ) < ρ W(ξ t j ): )()( )( j t i t j t WW W Prob: 22 )()( )( j t i t i t WW W )( j t W )( i t W 2 )()( i t j t WW Filtering Using SERP
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Simulation Parameters Error Function: r = 1 e Signal Estimate
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Simulation
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Future Directions - Workable explicit solution -Eliminate approximation errors in SERP particle evolve - Use IDEX as filter - More realistic manifolds - Cantilever equations - Enhance signal motion - Damped Harmonic Motion
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θ φ Other Observation Model
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Filtering with IDEX Goal: prove explicit solutions exist IDEX provides: Faster computation No inherent approximation error
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Background From Kouritzin and Remillard (2000): are 1-step nilpotent, h constraint holds
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Problem Description Two dimensional manifold in three space
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Conditions
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Equivalency By Ito’s formula and martingale theory: (1)
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Results Conjecture: Φ exists iff (2) where (2)
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Sketch of Proof Assuming that Φ exists, then (2) is equivalent to two-step nilpotentcy Apply chain rule Simplify equation
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Sketch of Proof Cont. If (2) holds, and all σ m are two step nilpotent, then Φ exists Idea: find satisfying (3) (4) (5) (6) (7)
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Sketch of Proof Cont. Let Φ be such that Get dΦ is exact by (3-7) Future: construct (4-6), show they converge
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