Case Studies on Detection Using mmWave FMCW RADAR System

Author:

Prakash Gummadi Surya1,Chandra W.1,Mehta Shilpa2ORCID,Kumar Rupesh1

Affiliation:

1. SRM University, India

2. Auckland University of Technology, New Zealand

Abstract

The content of this chapter provides a thoughtful analysis of case studies that highlight the detection capabilities of FMCW radar systems operating in mmWave configurations. The case studies demonstrate how mmWave FMCW radar technology may be used to detect objects, motions, and changes in both line of sight and non-line of sight settings with accuracy, and efficiency. Each case study explores the unique difficulties presented by the application environment, which can include anything from identifying impediments in automotive safety systems to detecting minute movements for vital sign monitoring in healthcare. The steps for detecting different gesture recognition using IWR 1843 BOOST FMCW radar system and its processing are focussed upon. The document highlights the technology's excellent resolution, motion sensitivity, and adaptability to a variety of challenging environments in LoS and NLoS scenarios and with the technical details of operating mmWave radars, including signal processing methods, machine learning algorithms, and mitigating interference from surrounding objects.

Publisher

IGI Global

Reference49 articles.

1. IoT-ready millimeter-wave radar sensors.;W. A.Ahmad;2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT),2020

2. Hand Gesture Recognition Using an IR-UWB Radar with an Inception Module-Based Classifier

3. Machine learning for healthcare radars: Recent progresses in human vital sign measurement and activity recognition.;S.Ahmed;IEEE Communications Surveys and Tutorials,2023

4. Hand Gestures Recognition Using Radar Sensors for Human-Computer-Interaction: A Review

5. Amar, R., Alaee-Kerahroodi, M., & Shankar, M. B. (2021, June). FMCW-FMCW interference analysis in mm-wave radars; an indoor case study and validation by measurements. In 2021 21st International Radar Symposium (IRS) (pp. 1-11). IEEE.

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