https://github.com/taherfattahi/car-tracking-kalman-filter
Ego and Target Car Tracking with LiDAR Measurements Using Kalman Filter
https://github.com/taherfattahi/car-tracking-kalman-filter
Last synced: 8 months ago
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Ego and Target Car Tracking with LiDAR Measurements Using Kalman Filter
- Host: GitHub
- URL: https://github.com/taherfattahi/car-tracking-kalman-filter
- Owner: taherfattahi
- License: mit
- Created: 2025-02-11T08:57:29.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2025-02-11T09:08:20.000Z (8 months ago)
- Last Synced: 2025-02-11T10:23:58.993Z (8 months ago)
- Language: Python
- Size: 249 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Ego and Target Car Tracking with LiDAR Measurements Using Kalman Filter
Simulate a real-world scenario where an ego vehicle (your car) tracks a target vehicle (the car ahead) using noisy LiDAR distance measurements and a Kalman filter. The simulation visualizes the positions of both vehicles on a road and displays the estimated relative state (distance and velocity) of the target vehicle in real time.
## Overview
In this simulation:
- **Ego Vehicle:** Represents your car that moves at a constant speed.
- **Target Vehicle:** The car ahead which also moves at a constant speed (possibly different from the ego vehicle).
- **LiDAR Measurements:** The distance between the two vehicles is measured using simulated LiDAR data with added Gaussian noise.
- **Kalman Filter:** Implements a 1D Kalman filter to estimate the relative state (distance and velocity) between the target and ego vehicles based on noisy LiDAR measurements.
## Requirements
- Python 3.x
- NumPy
- Matplotlib
You can install the required packages via pip:
```bash
pip install numpy matplotlib
```
## Usage
Run the simulation by executing the Python script:
```bash
python kalman_filter.py
```