Metadata-Version: 2.4
Name: awr2944-dca-lab
Version: 0.1.0
Summary: Research toolkit for AWR2944EVM + DCA1000EVM raw ADC radar capture workflows.
Project-URL: Repository, https://github.com/mahdi-kh1265/awr2944-fmcw-radar
Author: Mahdi Khamseh
License: MIT License
        
        Copyright (c) 2026 Mahdi Khamseh
        
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License-File: LICENSE
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
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Description-Content-Type: text/markdown

# awr2944-fmcw-radar

A Python research toolkit for TI AWR2944EVM + DCA1000EVM raw ADC radar captures.

This package provides a robust, native direct-capture pipeline that is free from mmWave Studio GUI automation and Lua scripts.

## Installation

Install the base package via pip:

```bash
pip install awr2944-dca-lab
```

To include the optional MATLAB viewer bridge dependencies (Windows only), install with the `viewer` extra:

```bash
pip install "awr2944-dca-lab[viewer]"
```

## Prerequisites

This Python package controls and orchestrates external hardware and software. The following are external prerequisites and must be installed separately:
- **MATLAB** (Required for the `viewer` component)
- **TI mmWave SDK tools**
- **DCA1000 CLI software**

## Architecture

The production capture chain uses:
1. SDK Demo UART CLI for radar configuration
2. TI DCA1000 CLI utilities (external dependency) for FPGA initialization
3. Native direct UDP capture with zero-copy stream processing and metadata logging
4. Sequence/counter validation and DCA depadding
5. Canonical ADC cube extraction
6. Python DSP and standalone MATLAB viewer `buildMmwsCompatibleShell.m`

Historical mmWave Studio GUI automation is available as an optional `legacy-mmws` dependency extra for compatibility and debugging.

## Reference documents

TI PDFs in `reference_docs/`:
- AWR2944EVM user guide (SPRUJ22C)
- DCA1000 + mmWave Studio raw capture training
- SWRA581B ADC raw data capture app report
- mmwaveSensing FMCW offline viewing deck (radar formulas)
