How lacania/receiver-state-hypothesis-selection works
This is a source-only archive for Receiver-State Hypothesis Selection in Doppler-only LEO positioning, accompanied by manual experiment and GNSS/GVINS analysis workflows. The principal workflow prepares observations, evaluates candidate receiver-state models, selects a hypothesis using validation and evidence, then evaluates results against truth or references where the protocol permits. The graph emphasizes documented M0–M14 selection, D2, and GNSS mechanisms. Wiring is conservative: sampled excerpts establish only some calls; unsampled capabilities are represented without speculative links.
Main entry points: native_runtime.py Runtime adapter · solvers.py State solvers · stage_methods.py D2 method stage · paper_exp01_run_holdout.py Holdout runner
Components 21
Positioning runtime
- Runtime adapter
src/flagship/native_runtime.py - Candidate models
src/leo_positioning/models.py - Candidate builders
src/leo_positioning/model_candidates.py - State solvers
src/leo_positioning/solvers.py - Trajectory models
src/leo_positioning/trajectory_models.py - Evidence gates
src/leo_positioning/model_evidence.py - Model scoring
src/leo_positioning/model_scoring.py - Hypothesis selector
manual_workflows/tree/flagship/21_v052_identity_repair/PAPER_FLAGSHIP_V052_INFORMATION_CRITERION_SELECTOR_PUBLICATIONIZATION/selector_parity/selector_spec_replay_v052.py - Quality diagnostics
src/leo_positioning/quality.py
Experiment evaluation
- D2 method stage
manual_workflows/tree/leo-c/tmp/d2_execution_r1/stage_methods.py - D2 truth evaluation
manual_workflows/tree/flagship/d2_corrected/source_snapshot/original_scripts/evaluate_d2_truth.py - Holdout runner
manual_workflows/tree/leo-c/_new_solver_lab/paper_draft/holdout_experiments/paper_exp01_run_holdout.py
GNSS workflows
- GNSS extraction
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/extract_gnss.py - Pilot selection
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/sports_field_pilot/scan_and_select.py - GPS-L1 wrapper
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/gps_l1_wrapper/wrapper.py - Fixed-state QA
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/gps_l1_wrapper/qa.py
Mechanism analysis
- Model adequacy
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/w120_model_adequacy_v1/analyze.py - Short-arc analysis
manual_workflows/tree/leo-c_new_solver_lab/GVINS_adapter/short_arc_identifiability_v1/evaluate_stage.py
Other components
- Researcher
- Observation inputs
- Selected state and metrics
Connections 25
- Researcher → Runtime adapter: runs workflow
- Observation inputs → Runtime adapter: provides input
- Runtime adapter → Candidate builders: builds candidates
- Candidate builders → State solvers: fits states
- State solvers → Candidate models: uses models
- State solvers → Trajectory models: uses trajectories
- Runtime adapter → Evidence gates: attaches evidence
- Runtime adapter → Model scoring: scores candidates
- Model scoring → Hypothesis selector: supplies scores
- Hypothesis selector → Selected state and metrics: selects hypothesis
- Runtime adapter → Quality diagnostics: computes quality
- Researcher → D2 method stage: runs stage
- D2 method stage → Runtime adapter: runs candidates
- D2 method stage → D2 truth evaluation: provides method output
- D2 truth evaluation → Selected state and metrics: evaluates against truth
- Researcher → Holdout runner: runs protocol
- Holdout runner → Runtime adapter: runs candidates
- Holdout runner → Selected state and metrics: writes evaluation
- Researcher → GNSS extraction: requests extraction
- GNSS extraction → Pilot selection: provides GNSS data
- Pilot selection → GPS-L1 wrapper: provides selected interval
- GPS-L1 wrapper → Fixed-state QA: provides forward outputs
- Fixed-state QA → Selected state and metrics: reports QA
- Researcher → Model adequacy: runs analysis
- Researcher → Short-arc analysis: runs analysis