Comprehensive Python library for phased array antenna modeling and visualization
Project description
Phased Array Antenna Modeling
A comprehensive Python library for computing and visualizing phased array antenna radiation patterns. Features 125x faster vectorized computations, multiple array geometries, advanced beamforming, and interactive 3D visualization.
Features
- High Performance: Vectorized array factor computation (125x faster than naive loops)
- Multiple Geometries: Rectangular, triangular, circular, cylindrical, spherical, sparse/thinned arrays
- Beamforming: Amplitude tapering (Taylor, Chebyshev, etc.), null steering, multi-beam
- Realistic Impairments: Mutual coupling, phase quantization, element failures, scan blindness
- Visualization: 2D matplotlib, interactive 3D Plotly, UV-space representation
- Subarray Support: Subarray-level beamforming with quantized phase shifters
- Data Export: CSV, JSON, and NumPy formats for patterns, weights, and geometry
Try it Online
Launch Interactive Web App - No installation required!
The Streamlit app provides an interactive interface for:
- Designing array geometries (rectangular, triangular, circular, concentric rings, elliptical)
- Beam steering with real-time pattern visualization
- Amplitude tapering with sidelobe comparison
- Impairment simulation (phase quantization, element failures, mutual coupling)
- UV-space pattern analysis
- Export data to CSV for further analysis
Installation
From GitHub (recommended)
pip install phased-array-modeling
With optional dependencies
# Include Plotly for 3D visualization
pip install "phased-array-modeling[plotting]"
# Include all optional dependencies
pip install "phased-array-modeling[full]"
For development
git clone https://github.com/jman4162/Phased-Array-Antenna-Model.git
cd Phased-Array-Antenna-Model
pip install -e ".[dev]"
Quick Start
import phased_array as pa
import numpy as np
# Create a 16x16 rectangular array with half-wavelength spacing
geom = pa.create_rectangular_array(16, 16, dx=0.5, dy=0.5)
# Wavenumber for normalized wavelength
k = pa.wavelength_to_k(1.0)
# Steering weights for 30 degree scan with Taylor taper
weights = pa.steering_vector(k, geom.x, geom.y, theta0_deg=30, phi0_deg=0)
weights *= pa.taylor_taper_2d(16, 16, sidelobe_dB=-30)
# Compute full 2D pattern
theta, phi, pattern_dB = pa.compute_full_pattern(geom.x, geom.y, weights, k)
# Plot
pa.plot_pattern_contour(np.rad2deg(theta), np.rad2deg(phi), pattern_dB,
title="16x16 Array - 30deg Scan with Taylor Taper")
Examples
Beam Steering
# Steer beam to theta=25 deg, phi=45 deg
weights = pa.steering_vector(k, geom.x, geom.y, theta0_deg=25, phi0_deg=45)
# Compute E-plane and H-plane cuts
angles, E_plane, H_plane = pa.compute_pattern_cuts(
geom.x, geom.y, weights, k,
theta0_deg=25, phi0_deg=45
)
Null Steering
# Place nulls at specific directions to reject interference
null_directions = [(20, 0), (-20, 0)] # (theta, phi) in degrees
weights = pa.null_steering_projection(
geom, k,
theta_main_deg=0, phi_main_deg=0,
null_directions=null_directions
)
Multiple Simultaneous Beams
# Create 3 simultaneous beams
beam_directions = [(0, 0), (25, 0), (25, 180)]
weights = pa.multi_beam_weights_superposition(
geom, k, beam_directions,
amplitudes=[1.0, 0.7, 0.7]
)
Circular/Conformal Arrays
# Cylindrical array
geom_cyl = pa.create_cylindrical_array(
n_azimuth=16, n_vertical=8,
radius=2.0, height=4.0
)
# Compute pattern accounting for element orientations
AF = pa.array_factor_conformal(theta, phi, geom_cyl, weights, k)
Phase Quantization Analysis
# Simulate 4-bit phase shifters
weights_quantized = pa.quantize_phase(weights, n_bits=4)
# Analyze effect on pattern
results = pa.analyze_quantization_effect(weights, geom, k, n_bits=4)
print(f"RMS phase error: {results['rms_error_deg']:.1f} degrees")
3D Interactive Visualization
# Create interactive 3D pattern plot
fig = pa.plot_pattern_3d_plotly(theta, phi, pattern_dB,
title="3D Radiation Pattern")
fig.show()
Documentation
Full Documentation on ReadTheDocs includes:
- Getting Started: Installation, quickstart guide, core concepts
- User Guides: Detailed tutorials for geometry, beamforming, impairments, wideband, and visualization
- API Reference: Complete reference for all functions with examples
- Cookbook: Practical recipes for hardware engineers, systems engineers, and researchers
- Theory Background: Mathematical foundations for array analysis
For hands-on learning, see the demo notebook which covers:
- Basic array factor computation
- Beam steering
- Performance benchmarking
- Amplitude tapering comparison
- Array geometries (rectangular, triangular, circular, etc.)
- Null steering
- Multiple simultaneous beams
- Phase quantization effects
- Element failure analysis
- UV-space visualization
- 3D Plotly visualization
- Conformal array patterns
- Mutual coupling effects
- Subarray beamforming
Package Structure
phased_array/
├── core.py # Vectorized AF, FFT, steering, element patterns
├── geometry.py # Array geometries and subarray architectures
├── beamforming.py # Tapering, null steering, multi-beam
├── impairments.py # Coupling, quantization, failures, scan blindness
├── visualization.py # 2D, 3D Plotly, UV-space plotting
└── utils.py # Coordinate transforms, helpers
Requirements
- Python 3.8+
- NumPy >= 1.20.0
- Matplotlib >= 3.5.0
- SciPy >= 1.7.0
- Plotly >= 5.0.0 (optional, for 3D visualization)
Running Tests
pytest tests/ -v
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
License
This project is licensed under the MIT License - see the LICENSE file for details.
Citation
If you use this library in your research, please cite:
@software{phased_array,
author = {Hodge, John},
title = {Phased Array Antenna Modeling},
url = {https://github.com/jman4162/Phased-Array-Antenna-Model},
year = {2024}
}
Contact
John Hodge - jah70@vt.edu
Project Link: https://github.com/jman4162/Phased-Array-Antenna-Model
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file phased_array_modeling-1.3.0.tar.gz.
File metadata
- Download URL: phased_array_modeling-1.3.0.tar.gz
- Upload date:
- Size: 73.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1be5b17959c7eb7c714ac2baa1678e20e7a5f49aaa02dfd5244423787489a2da
|
|
| MD5 |
245e457d72c96d838122d0987497ecc3
|
|
| BLAKE2b-256 |
b0373a20bd36e76ec7d1b1759b771b2a6af7663fd69d281f39193bb849301cbb
|
File details
Details for the file phased_array_modeling-1.3.0-py3-none-any.whl.
File metadata
- Download URL: phased_array_modeling-1.3.0-py3-none-any.whl
- Upload date:
- Size: 62.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5a056b89854b3ffa1fa27103fd20c8b263cebc8232fe67a205645177ab7a65ee
|
|
| MD5 |
7e1079d84a600d70a1ef08d1b735303d
|
|
| BLAKE2b-256 |
816c05de02e974121c79fd4550ac83c2904d3d4913d85c43d54229f991a265f5
|