CW Doppler Radar as Occupancy Sensor: A Comparison of Different Detection Strategies

Abstract

Indoor occupancy sensing is a crucial problem in several application fields that have progressed from intrusion detection systems to automatic control of lighting, heating, air conditioning and many other presence-related loads. Continuous wave Doppler radar is a simple technology to face this problem due to its capability to detect human body movements (e.g., walk, run) and small chest wall vibrations associated to the cardiorespiratory activity. This work deals with a radar prototype operating at 2.4 GHz as a real-time occupancy sensor. The emphasis is on data processing approaches devoted to extract useful information from raw radar signal. Three different strategies, designed to detect human presence in indoor environments, are considered and the main goal is the assessment and comparison of their performance against experimental data collected in controlled conditions. The first strategy is based on the analysis of the standard deviation of the radar signal in time-domain; whereas the second one exploits the histogram of the time-varying signal amplitude. Finally, a third strategy based on an energy measure of the received signal Doppler spectrum is considered. The proposed detection algorithms are optimized through a set of calibration measurements and their performances and robustness are assessed by laboratory trials.

Unobtrusive occupancy and vital signs sensing for human building interactive systems

“…The research published in recent years on occupancy sensing using Doppler radar indicates that activity and physiological sensing could be used to remotely evaluate occupant response to environmental conditions, which would lead to major changes in HBI. Gennarelli et al 16 achieve an occupancy/vacancy accuracy of greater than 96% by applying standard deviation, histogram and Doppler spectrum energy methods to a continuous wave quadrature Doppler radar for real-time occupancy sensing in indoor environments. Lurz et al 17 emulate human respiration using a metallic plate mounted on a linear stage and demonstrate a human subject at null point still can be detected with a single channel low-power 24 GHz receiver.…”

“…While the progress in works cited above is notable, these works have some limitations, such as short experimental duration (up to 60 s for [16][17][18][19][20] ), the inferior sensitivity of passive radar systems for detecting stationary persons 21,22,23 , and detection of stationary persons only at 2-3 m from the sensor 16,17 . The True Presence Occupancy Detection Sensor (TruePODS™) presented in this paper is a Doppler radar-sensor that detects physiological motion to indicate whether a space is occupied or vacant 24 .…”

A novel target state detection method for accurate cardiopulmonary signal extraction based on FMCW radar signals

“…The remote monitoring of vital signs of the radar system is more and more widely used. Radar can detect human presence in indoor environments ( Mercuri et al, 2013 ; Gennarelli et al, 2022 ). Radar can track the periodic movement of body parts caused by breathing, which can be used for system diagnosis of breathing problems such as apnea ( Sun, 2019 ; Islam et al, 2021 ; Ishrak et al, 2023 ).…”

“…The radars currently used for vital signs detection include frequency-modulated continuous wave (FMCW) radar ( He et al, 2017 ; Ahmad et al, 2018 ), ultra-wideband (UWB) radar ( Deng et al, 2019 ; Yang et al, 2021 ; Sharma et al, 2023 ), continuous wave (CW) radar ( Hong et al, 2018 ; Gennarelli et al, 2022 ), etc. The FMCW radar has a wide range of applications for continuous non-contact vital sign monitoring in a variety of scenarios.…”

Characterization Technique for a Doppler Radar Occupancy Sensor

“…To overcome the drawbacks of traditional PIR and US sensors, new technologies, such as hybrid (combining PIR and ultrasound in one sensor) [3], infrared time-of-flight [4], video [5], CO 2 [6], thermopile array [7,8], chair sensors [9], and radar sensors [7,[10][11][12][13][14][15][16] have been in development, with some of them emerging in the market. New approaches to signal processing are also being developed to improve the accuracy of occupancy detection, reduce false-vacancy signals, and add features such as count estimation.…”