This project demonstrates a basic radar signal processing system using Fast Fourier Transform (FFT) algorithms in Python. The system simulates radar pulse transmission, target reflection, noise addition, and frequency-domain analysis to detect signal peaks and estimate target distance.
The project is designed for understanding Digital Signal Processing (DSP), radar fundamentals, and FFT-based signal detection techniques commonly used in communication systems, automotive radar, and defense applications.
- Simulate radar signal transmission and reception
- Implement FFT-based signal analysis
- Detect target signal peaks in frequency spectrum
- Estimate target distance using signal delay
- Analyze noisy radar signals for detection accuracy
- Radar pulse signal generation
- Simulated target reflection
- Noise addition for realistic conditions
- FFT implementation using NumPy
- Peak frequency detection
- Distance estimation
- Time-domain and frequency-domain visualization
- Python
- NumPy
- Matplotlib
- Radar Signal Processing
- Fast Fourier Transform (FFT)
- Frequency Spectrum Analysis
- Peak Detection
- Signal Sampling
- Noise Analysis
- Distance Estimation
- Generate radar transmitted signal
- Simulate reflected signal from target
- Add random noise to received signal
- Apply FFT to received signal
- Detect frequency peaks
- Estimate target distance
- Plot waveform and FFT spectrum
x(t) = A sin(2πft)
Where:
- A = Amplitude
- f = Frequency
- t = Time
d = (c × t) / 2
Where:
- d = Target distance
- c = Speed of light
- t = Signal delay time
X(k) = Σ x(n)e^(-j2πkn/N)
FFT converts the signal from time domain to frequency domain for easier detection.
Radar-FFT-Project/ │ ├── radar.py ├── README.md └── Figure_1.jpeg/
Download and install Python: https://www.python.org/
Open terminal or command prompt:
pip install numpy matplotlib
Run the Python file using:
python radar.py
The program displays:
- Detected peak frequency
- Peak amplitude
- Estimated target distance
It also generates graphs for:
- Transmitted radar signal
- Received noisy signal
- FFT frequency spectrum
Detected Peak Frequency : 50.00 Hz
Peak Amplitude : 504.96
Estimated Target Distance : 6000000 meters
- Defense radar systems
- Automotive radar
- Air traffic monitoring
- Drone detection
- Weather radar systems
- Signal intelligence systems
- Simple FFT implementation
- Easy visualization of radar signals
- Useful for DSP learning
- Realistic noise simulation
- Low computational complexity using FFT
- Basic radar simulation only
- No Doppler velocity estimation
- Limited range resolution
- Sensitive to high noise conditions
- FMCW radar implementation
- Doppler shift detection
- CFAR target detection
- Real-time signal processing
- FPGA implementation
- SDR (Software Defined Radio) integration
Through this project, the following concepts were learned:
- FFT and spectral analysis
- Radar signal fundamentals
- Digital signal processing
- Noise handling techniques
- Frequency-domain detection methods
- Python-based signal simulation
This project successfully demonstrates radar signal detection using FFT algorithms in Python. The system analyzes noisy radar reflections, detects frequency peaks, and estimates target distance efficiently using frequency-domain signal processing techniques.
Ashish Yadav Nit Jamshedpur Radar Signal Detection Using FFT (Simulation)