feat: Complete Rust port of WiFi-DensePose with modular crates

Major changes:
- Organized Python v1 implementation into v1/ subdirectory
- Created Rust workspace with 9 modular crates:
  - wifi-densepose-core: Core types, traits, errors
  - wifi-densepose-signal: CSI processing, phase sanitization, FFT
  - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch)
  - wifi-densepose-api: Axum-based REST/WebSocket API
  - wifi-densepose-db: SQLx database layer
  - wifi-densepose-config: Configuration management
  - wifi-densepose-hardware: Hardware abstraction
  - wifi-densepose-wasm: WebAssembly bindings
  - wifi-densepose-cli: Command-line interface

Documentation:
- ADR-001: Workspace structure
- ADR-002: Signal processing library selection
- ADR-003: Neural network inference strategy
- DDD domain model with bounded contexts

Testing:
- 69 tests passing across all crates
- Signal processing: 45 tests
- Neural networks: 21 tests
- Core: 3 doc tests

Performance targets:
- 10x faster CSI processing (~0.5ms vs ~5ms)
- 5x lower memory usage (~100MB vs ~500MB)
- WASM support for browser deployment

v1/tests/unit/test_phase_sanitizer.py

@@ -0,0 +1,107 @@
+import pytest
+import numpy as np
+from unittest.mock import Mock, patch
+from src.core.phase_sanitizer import PhaseSanitizer
+
+
+class TestPhaseSanitizer:
+    """Test suite for Phase Sanitizer following London School TDD principles"""
+    
+    @pytest.fixture
+    def mock_phase_data(self):
+        """Generate synthetic phase data for testing"""
+        # Phase data with unwrapping issues and outliers
+        return np.array([
+            [0.1, 0.2, 6.0, 0.4, 0.5],  # Contains phase jump at index 2
+            [-3.0, -0.1, 0.0, 0.1, 0.2],  # Contains wrapped phase at index 0
+            [0.0, 0.1, 0.2, 0.3, 0.4]   # Clean phase data
+        ])
+    
+    @pytest.fixture
+    def phase_sanitizer(self):
+        """Create Phase Sanitizer instance for testing"""
+        return PhaseSanitizer()
+    
+    def test_unwrap_phase_removes_discontinuities(self, phase_sanitizer, mock_phase_data):
+        """Test that phase unwrapping removes 2π discontinuities"""
+        # Act
+        result = phase_sanitizer.unwrap_phase(mock_phase_data)
+        
+        # Assert
+        assert result is not None
+        assert isinstance(result, np.ndarray)
+        assert result.shape == mock_phase_data.shape
+        
+        # Check that large jumps are reduced
+        for i in range(result.shape[0]):
+            phase_diffs = np.abs(np.diff(result[i]))
+            assert np.all(phase_diffs < np.pi)  # No jumps larger than π
+    
+    def test_remove_outliers_filters_anomalous_values(self, phase_sanitizer, mock_phase_data):
+        """Test that outlier removal filters anomalous phase values"""
+        # Arrange - Add clear outliers
+        outlier_data = mock_phase_data.copy()
+        outlier_data[0, 2] = 100.0  # Clear outlier
+        
+        # Act
+        result = phase_sanitizer.remove_outliers(outlier_data)
+        
+        # Assert
+        assert result is not None
+        assert isinstance(result, np.ndarray)
+        assert result.shape == outlier_data.shape
+        assert np.abs(result[0, 2]) < 10.0  # Outlier should be corrected
+    
+    def test_smooth_phase_reduces_noise(self, phase_sanitizer, mock_phase_data):
+        """Test that phase smoothing reduces noise while preserving trends"""
+        # Arrange - Add noise
+        noisy_data = mock_phase_data + np.random.normal(0, 0.1, mock_phase_data.shape)
+        
+        # Act
+        result = phase_sanitizer.smooth_phase(noisy_data)
+        
+        # Assert
+        assert result is not None
+        assert isinstance(result, np.ndarray)
+        assert result.shape == noisy_data.shape
+        
+        # Smoothed data should have lower variance
+        original_variance = np.var(noisy_data)
+        smoothed_variance = np.var(result)
+        assert smoothed_variance <= original_variance
+    
+    def test_sanitize_handles_empty_input(self, phase_sanitizer):
+        """Test that sanitizer handles empty input gracefully"""
+        # Arrange
+        empty_data = np.array([])
+        
+        # Act & Assert
+        with pytest.raises(ValueError, match="Phase data cannot be empty"):
+            phase_sanitizer.sanitize(empty_data)
+    
+    def test_sanitize_full_pipeline_integration(self, phase_sanitizer, mock_phase_data):
+        """Test that full sanitization pipeline works correctly"""
+        # Act
+        result = phase_sanitizer.sanitize(mock_phase_data)
+        
+        # Assert
+        assert result is not None
+        assert isinstance(result, np.ndarray)
+        assert result.shape == mock_phase_data.shape
+        
+        # Result should be within reasonable phase bounds
+        assert np.all(result >= -2*np.pi)
+        assert np.all(result <= 2*np.pi)
+    
+    def test_sanitize_performance_requirement(self, phase_sanitizer, mock_phase_data):
+        """Test that phase sanitization meets performance requirements (<5ms)"""
+        import time
+        
+        # Act
+        start_time = time.time()
+        result = phase_sanitizer.sanitize(mock_phase_data)
+        processing_time = time.time() - start_time
+        
+        # Assert
+        assert processing_time < 0.005  # <5ms requirement
+        assert result is not None