- If possible, remove environment clutter from prior knowledge. A variety of techniques can be used here depending on the application. Typically, you can use doppler from radar to separate static and dynamic reflections. Another example is limiting the region of interest in your data.
- If your radar generates multiple returns from objects, you may need to cluster them (as shown in examples above) or use an extended object tracker. For an example on extended object tracker, refer to
Multiple Target Tracking using data coming from a real device
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I'm planning to develop a multiple target tracking system using data coming from a real radar device. Outputs of the device are 1. range data, 2 azimuth data. In other words, those are point cloud data output at frame rate and not labeled. In this case, which MATLAB functions should I use to realize the goal?
The tools I have are as follows.
- DSP System Toolbox
- Phased Array System Toolbox
- RF Toolbox
- Radar Toolbox
- Sensor Fusion and Tracking Toolbox
- Signal Processing Toolbox
I appreciate if someone gives me a hint to solve this question.
Prashant Arora on 2 Nov 2023
You may find the examples linked below useful. These show how to track objects using data from TI mmWave Radars.
In general, the workflow to use azimuth, range data would be
3. To bring your "azimuth, range" data to tracker objectDetection format, check out the following example.
Hope this helps.
More Answers (1)
recent works on 27 Oct 2023
To develop a multiple target tracking system using data from a real radar device in MATLAB, you have a good set of toolboxes that can help you with various aspects of radar signal processing and target tracking. Here's a high-level overview of how you can use these toolboxes to achieve your goal:
- DSP System Toolbox and Signal Processing Toolbox: You can use these toolboxes to preprocess and filter the raw radar data, which includes range and azimuth data. You may need to perform filtering, noise reduction, and data calibration to improve the quality of the data.
Radar Signal Processing:
- Phased Array System Toolbox and RF Toolbox: These toolboxes can help you model and simulate phased-array antennas and radar systems. You can use them to create radar waveform designs, simulate radar scenarios, and perform beamforming and angle estimation.
Radar Data Extraction:
- Radar Toolbox: Use this toolbox to extract essential radar parameters from the data, such as target range, azimuth, and Doppler information. You can also explore clutter and interference rejection techniques.
Multiple Target Tracking:
- Sensor Fusion and Tracking Toolbox: This toolbox is crucial for multiple target tracking. It provides various tracking algorithms and tools for data association, track initialization, and state estimation. You can choose from a variety of tracking filters (e.g., Kalman filter, particle filter) and data association methods (e.g., nearest neighbor, probabilistic data association) to implement your tracking system.
Visualization and Validation:
- Use MATLAB's built-in functions and plotting capabilities to visualize the tracking results and validate the performance of your tracking system. You can also use the tools provided by the aforementioned toolboxes to generate plots and displays.