Simulation of Pulse Compression, MTI, and MTD for Radar 8-Pulse Echo Data

This paper presents a radar signal processing study involving pulse compression, MTI, and MTD simulations on eight pulse echo datasets. Pulse compression, implemented through matched filtering techniques (typically using convolution with reference waveforms), enhances radar resolution and signal-to-noise ratio. MTI algorithms employ digital filtering methods like delay-line cancellers to suppress clutter from stationary objects. MTD processing combines Doppler filtering using FFT-based spectral analysis with Constant False Alarm Rate (CFAR) detection for moving target identification. The simulation structure involves generating pulse echoes with target and clutter models, applying windowing functions for sidelobe reduction, and implementing detection logic with threshold adaptation. By simulating these signal processing chains, we evaluate radar performance parameters including detection probability, false alarm rates, and resolution capabilities. This research contributes to radar technology advancement by providing implementable processing frameworks and performance validation methodologies for modern radar systems.