This lecture offers a comprehensive overview of the evolution, principles, and cutting-edge applications of radar technology. We trace radar's development from its early days to modern advancements, emphasizing the integration of digital and statistical signal processing with artificial intelligence (AI). Key topics include the history of radar, modern techniques such as FMCW (Frequency Modulated Continuous Wave) and Pulse Doppler radars, and AI's transformative role in detection, tracking, classification, and decision-making.

We delve into the technical foundations of radar signal processing, explaining concepts like frequency modulation, signal mixing, and range-Doppler processing. The lecture also covers the significant AI applications in radar, such as clutter suppression, target classification, and adaptive waveform optimization. Challenges like the need for large training datasets, model interpretability, and robust AI systems are discussed alongside solutions like data augmentation and generative models.

Through detailed explanations and high-level block diagrams, the lecture aims to provide a solid understanding of radar systems' operational principles and AI's role in enhancing their capabilities. This foundational knowledge prepares participants for deeper exploration of these technologies in subsequent modules.