Optimize association algorithm with better assignment (post-MVP) #12
Description
Overview
Replace greedy nearest neighbor association with optimal assignment algorithm.
Priority Revision
DOWNGRADED from MVP Critical → Post-MVP Enhancement
Reason: The current greedy association may be adequate for MVP. The real problem is having any radar-only association (#20), not optimizing the assignment algorithm.
Current State
- Simple greedy nearest neighbor association in Stone Soup tracker
- Basic cost matrix with distance-based costs
- Works adequately with current ADS-B data
Target State (Post-MVP)
- Optimal assignment algorithm (Hungarian algorithm)
- Better cost metrics incorporating uncertainty
- Improved association accuracy
Dependencies
- BLOCKED by Implement RadarOnlyAssociator for pure radar tracking #20 - Need basic radar-only association working first
- Should be evaluated after radar-only operation is proven
Reality Check
The flowchart shows "Nearest Neighbors" as part of the association process, suggesting the current approach may be acceptable. The issue isn't the assignment algorithm, it's the lack of radar-only association capability.
Benefits (Post-MVP)
- Optimal assignments instead of greedy selection
- Better overall association quality
- Foundation for complex multi-target scenarios
Note: This is an optimization of association that doesn't exist yet for radar-only mode. Get basic radar association working first, then optimize.