Methods and techniques in deep learning advancements in mmwave radar solutions - Santra, Avik (Hoboken, New Jersey John Wiley & Sons, Inc., 2023)
"The advent of deep learning has transformed many fields and resulted in state-of-art solutions in computer vision, natural language processing and speech processing, etc. However, the application of deep learning algorithms to radars is still by and large at its nascent stage. A radar system consists of two parts: first, the radar hardware, including the RF transceiver, waveform generator, receiver unit, antenna and system packaging. State-of-art SiGe and CMOS are candidate technologies for mm-wave short-range radars and offer flexibility for integration and smaller form-factor. Second part is the sensing aspect, which relies on signal processing or deep learning algorithms that parses the radar return echo into meaningful target information facilitating a desired application"--
Includes bibliographical references and index.
Keywords: Deep learning (Machine learning); Millimeter wave radar -- Data processing; Radar receiving apparatus -- Data processing; Radar targets -- Identification -- Data processing