Simple Radar Pipeline Application

Authors: Cliff Burdick (NVIDIA)
Supported platforms: x86_64
Last modified: March 18, 2025
Language: Python
Latest version: 1.0
Minimum Holoscan SDK version: 0.4.0
Tested Holoscan SDK versions: 0.4.0
Contribution metric: Level 2 - Trusted

This demonstration walks the developer through building a simple radar signal processing pipeline, targeted towards detecting objects, with Holoscan. In this example, we generate random radar and waveform data, passing both through: 1. Pulse Compression 2. Moving Target Indication (MTI) Filtering 3. Range-Doppler Map 4. Constant False Alarm Rate (CFAR) Analysis

While this example generates 'offline' complex-valued data, it could be extended to accept streaming data from a phased array system or simulation via modification of the SignalGeneratorOperator.

The output of this demonstration is a measure of the number of pulses per second processed on GPU.

The main objectives of this demonstration are to: - Highlight developer productivity in building an end-to-end streaming application with Holoscan and existing GPU-Accelerated Python libraries - Demonstrate how to construct and connect isolated units of work via Holoscan operators, particularly with handling multiple inputs and outputs into an Operator - Emphasize that operators created for this application can be re-used in other ones doing similar tasks

Running the Application

Prior to running the application, the user needs to install the necessary dependencies. This is most easily done in an Anaconda environment.

conda create --name holoscan-sdr-demo python=3.8
conda activate holoscan-sdr-demo
conda install -c conda-forge -c rapidsai -c nvidia cusignal
pip install holoscan

The simple radar signal processing pipeline example can then be run via

python applications/simple_radar_pipeline/simple_radar_pipeline.py