feat: preamble detection + frequency fingerprinting - iteration 3/5
Implements multi-factor scoring pipeline for improved RF device identification:
- Score = Timing(30%) + Frequency(25%) + BitCount(20%) + Preamble(15%) + Stats(10%)
New Components:
- src/matcher/preamble_detector.py: Detects 4 pattern types (long_burst, alternating, sync_word, custom)
- src/matcher/frequency_fingerprint.py: ISM band classification (315/433/868/915 MHz) for protocol filtering
- Integration: Updated pattern_decoder.py with multi-factor scoring
Features:
- Preamble detection with 4 methods (long burst, alternating, sync word, repetition)
- Frequency-based protocol filtering (reduces search space from 299 to ~20-30 candidates)
- Multi-factor confidence scoring combining timing, frequency, bit count, preamble, and statistics
- Sorted sync word matching (longest first to avoid substring matches)
Test Coverage:
- 15 new tests for preamble detection and frequency fingerprinting
- Total: 56 tests passing (41 existing + 15 new)
Results:
- Improved matching accuracy through multi-factor scoring
- Reduced protocol search space via frequency pre-filtering
- Better handling of noisy signals through preamble validation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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