Pulse Compression of Linear Frequency Modulated Signals Implementation

This classic radar signal processing program covers the following key techniques and concepts:

1. Pulse Compression of Linear Frequency Modulated Signals: We explore in detail how to process linear frequency modulated signals using pulse compression techniques to enhance radar system resolution and measurement accuracy. Implementation typically involves matched filtering where the transmitted chirp signal is correlated with its time-reversed complex conjugate, using Fast Fourier Transform (FFT) operations for efficient computation in MATLAB or Python.

2. Moving Target Detection: We study how radar systems detect and track moving targets. This includes implementing signal processing algorithms such as Doppler processing, constant false alarm rate (CFAR) detection, and tracking techniques like Kalman filters. The code implementation typically involves range-Doppler processing where 2D FFT operations separate targets based on their range and velocity characteristics.

3. Moving Target Indication: We demonstrate how to visualize detected moving targets on radar displays, enabling operators to intuitively observe and analyze target trajectories and characteristics. This involves implementing display algorithms that can highlight moving targets while suppressing clutter, often using techniques like MTI filters that employ recursive delay-line cancellers to remove stationary echoes.

By deeply studying these techniques and concepts, you will gain comprehensive understanding of radar system working principles and application domains, providing a solid foundation for your radar-related learning and research endeavors. The program includes practical code implementations showing real-time signal processing pipeline from raw radar data to target visualization.