Fix: Markdown linting issues

- Add blank lines around headings and lists
- Fix bare URLs in headings
- Add trailing newlines to files
- Comply with markdownlint standards

Author: challgren

CHANGELOG.md

@@ -8,6 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [1.0.0] - 2025-01-06
 
 ### Added
+
 - Initial release of Aircraft Circle pattern detection system
 - Real-time circle pattern detection for training and holding patterns
 - Grid pattern detection for survey and search operations
@@ -24,6 +25,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Comprehensive documentation
 
 ### Features
+
 - Circle Detection
   - Configurable radius range (0.5-10km default)
   - Minimum turn detection (1.5 turns default)
@@ -44,6 +46,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - Interactive controls
 
 ### Technical
+
 - Python 3.8+ support
 - Flask web framework
 - Leaflet.js mapping
@@ -53,6 +56,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - CSV data persistence
 
 ### Documentation
+
 - Comprehensive README
 - Docker deployment guide
 - Configuration reference
@@ -64,11 +68,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## Future Releases
 
 ### [Planned Features]
+
 - Additional pattern types (figure-8, racetrack)
 - Email/webhook notifications
 - Pattern statistics dashboard
 - Machine learning pattern prediction
 - Multi-language support
 - Mobile responsive design
 - API endpoints for integration
-- Prometheus metrics export
+- Prometheus metrics export

CONTRIBUTING.md

@@ -5,6 +5,7 @@ Thank you for your interest in contributing to Aircraft Circle! This document pr
 ## Code of Conduct
 
 By participating in this project, you agree to abide by our code of conduct:
+
 - Be respectful and inclusive
 - Welcome newcomers and help them get started
 - Focus on constructive criticism
@@ -52,13 +53,15 @@ pip install black flake8 pytest
 #### Development Workflow
 
 1. Create a feature branch:
+
    ```bash
    git checkout -b feature/your-feature-name
    ```
 
 2. Make your changes following our coding standards
 
 3. Test your changes:
+
    ```bash
    # Run the application
    python app.py --test
@@ -71,12 +74,14 @@ pip install black flake8 pytest
    ```
 
 4. Commit your changes:
+
    ```bash
    git add .
    git commit -m "Add: brief description of changes"
    ```
 
 5. Push to your fork:
+
    ```bash
    git push origin feature/your-feature-name
    ```
@@ -114,6 +119,7 @@ def calculate_circle_radius(positions: List[Position]) -> float:
 ### Commit Messages
 
 Use clear, descriptive commit messages:
+
 - `Add: new feature description`
 - `Fix: bug description`
 - `Update: component description`
@@ -230,6 +236,7 @@ docker buildx build \
 ## Recognition
 
 Contributors will be recognized in:
+
 - README.md acknowledgments
 - Release notes
 - Project documentation

README.md

@@ -11,19 +11,22 @@ Real-time aircraft pattern detection system that monitors TAR1090 feeds to ident
 ## 🎯 Features
 
 ### Pattern Detection
+
 - **Circle Detection**: Identifies aircraft flying in circular patterns (training, holding, orbits)
 - **Grid Detection**: Detects survey/search grid patterns, mapping flights, and search & rescue operations
 - **Real-time Monitoring**: Continuously analyzes aircraft movements from TAR1090 data feeds
 - **Historical Tracking**: Maintains comprehensive logs of all detected patterns with TAR1090 replay links
 
 ### Web Interface
+
 - **Live Map View**: Real-time visualization of aircraft and detected patterns
 - **TAR1090-style Icons**: Aircraft displayed with type-appropriate icons and altitude-based coloring
 - **Track History**: Flight path visualization with altitude-based color coding
 - **Pattern History Page**: Browse and filter all historical pattern detections
 - **Interactive Controls**: Toggle aircraft display, tracks, and pattern overlays
 
 ### Data & Integration
+
 - **CSV Logging**: Automatic logging of all detections for analysis
 - **TAR1090 Integration**: Direct links to view patterns in TAR1090 with proper time ranges
 - **Multi-source Support**: Works with any TAR1090-compatible data source
@@ -94,27 +97,35 @@ python app.py --server http://your-tar1090:8080 --web
 ### Detection Parameters
 
 #### Circle Detection
+
 | Variable | Description | Default |
 |----------|-------------|---------|
 | `MIN_RADIUS` | Minimum circle radius (km) | `0.5` |
 | `MAX_RADIUS` | Maximum circle radius (km) | `10` |
 | `MIN_TURNS` | Minimum number of turns | `1.5` |
 
 #### Grid Detection
+
 | Variable | Description | Default |
 |----------|-------------|---------|
 | `MIN_GRID_LEGS` | Minimum parallel legs | `3` |
 | `MIN_LEG_LENGTH` | Minimum leg length (km) | `2.0` |
 
 ## 🖥️ Web Interface
 
-### Live View (http://localhost:8888)
+### Live View
+
+Access at: `http://localhost:8888`
+
 - Real-time aircraft positions with TAR1090-style icons
 - Live pattern detection with visual overlays
 - Interactive controls for display options
 - Auto-centering on new pattern detections
 
-### History View (http://localhost:8888/history)
+### History View
+
+Access at: `http://localhost:8888/history`
+
 - Browse all historical pattern detections
 - Filter by date range, pattern type, and callsign
 - Visual timeline of detection activity
@@ -124,12 +135,14 @@ python app.py --server http://your-tar1090:8080 --web
 ## 📊 Data Output
 
 ### CSV Files
+
 Pattern detections are automatically logged to CSV files in the data directory:
 
 - `circle_detections.csv` - All circular pattern detections
 - `grid_detections.csv` - All grid pattern detections
 
 ### CSV Fields
+
 - Timestamp, Aircraft ID, Callsign
 - Pattern characteristics (radius, turns, coverage area)
 - Position data (center lat/lon)
@@ -139,7 +152,9 @@ Pattern detections are automatically logged to CSV files in the data directory:
 ## 🐳 Docker Deployment
 
 ### Multi-Architecture Support
+
 The container supports multiple architectures:
+
 - `linux/amd64` - Standard x86-64
 - `linux/arm64` - 64-bit ARM (Raspberry Pi 4, etc.)
 - `linux/arm/v7` - 32-bit ARM
@@ -201,13 +216,15 @@ Options:
 ## 📈 Pattern Detection Logic
 
 ### Circle Detection Algorithm
+
 1. Analyzes aircraft track points to identify curved paths
 2. Calculates center point and radius of potential circles
 3. Counts completed turns (360° rotations)
 4. Validates against minimum radius and turn requirements
 5. Logs detection with TAR1090 replay link
 
 ### Grid Detection Algorithm
+
 1. Identifies parallel flight segments
 2. Analyzes heading changes between legs
 3. Validates grid spacing and coverage area
@@ -249,4 +266,4 @@ This project is licensed under the MIT License - see the [LICENSE](LICENSE) file
 
 ---
 
-Made with ❤️ for the aviation and SDR community
+Made with ❤️ for the aviation and SDR community