Detection of Human Breathing in Non-Line-of-Sight Region by Using mmWave FMCW Radar

Li, Gen; Ge, Yun; Wang, Yiyu; Chen, Qingwu; Wang, Gang

doi:10.1109/tim.2022.3208266

Cited by 25 publications

(9 citation statements)

References 44 publications

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“…Drones and unmanned aerial vehicles: LFMCW radar can be used for obstacle detection, collision avoidance, and terrain mapping in unmanned aerial vehicles to enhance flight safety and navigation capabilities [11][12][13][14][15]; 3. Defense systems: LFMCW radar is used for target detection and tracking in military and defense applications, such as target identification, missile defense, and surveillance systems [16][17][18][19][20]; 4. Industrial applications: LFMCW radar can be used for distance measurement, displacement detection, object identification, and motion tracking in industrial settings for automation control and robotics applications [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Implementation of Signal Processing for LFM Radar Using DSK 6713

Mon

2023

Electronics

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This research aims to propose a comprehensive simulation and implementation methodology for LFM (Linear Frequency Modulated) Radar Signal Processing and its application, using digital signal processing techniques on the DSP Starter Kit (DSK) 6713 board. The motivation behind this study is to develop control software based on MATLAB R14 and SIMULINK to model various system software tasks, including detection, A/D conversion, Fast Fourier Transform (FFT), modulation, accumulation, decision-making, and target detection. The simulations are categorized into two groups: ideal beat frequency and parameterized beat frequency. We introduce several important terminologies for consideration, including pulse compression, SNR, matched filter, Doppler effect, and more. The use of real-time data exchange (RTDX) will facilitate the generation of input data and enable real-time calculations for outputs, leading to the creation of machine code for the DSP chip. This process aims to ensure data verification calculations and enhance the credibility and performance of the proposed methodology. By conducting thorough simulations, verification, and practical testing, the study demonstrates the satisfactory credibility and performance of the developed method. Using this research, we aim to contribute to the advancement of LFM Radar Signal Processing and enable its efficient implementation using digital signal processing techniques on the DSP Starter Kit (DSK) 6713 board.

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Section: Introductionmentioning

confidence: 99%

Simulation and Implementation of Signal Processing for LFM Radar Using DSK 6713

Mon

2023

Electronics

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“…Radar on the other hand does not have the above-named restrictions and has therefore become an interesting alternative for this purpose. As a sensor, radar works in a contactless fashion but is not restricted to unobstructed line-of-sights, which is why so-called through-wall-radars have been used in search-and-rescue operations and non-line of sight propagation approaches have been demonstrated, for example for detecting around the corner [5], [6], [7]. Another essential advantage of radar is that it is, by nature, capable of measuring motion directly by exploiting the Doppler effect.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Radar-Based Continuous Human Activity Recognition

Ullmann¹,

Guendel

Kruse

et al. 2023

IEEE J. Microw.

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Radar-based human motion and activity recognition is currently a topic of great research interest, as the aging population increases and older individuals prefer an independent lifestyle. This technology has a wide range of applications, such as fall detection in assisted living, gesture recognition for human-machine interfaces, and many more. Numerous studies exist on various approaches for radar-based activity capture and classification. However, most of these employ rather artificial data, often obtained in laboratory environments, and typically collected under particular conditions. Specifically, most research so far has aimed at distinguishing a predefined set of single activities with a defined start, stop and duration. This paper aims at drawing the attention to a so far less researched issue, one that will be of vital importance for future real-world application of radar-based human activity recognition: continuous activity recognition, i.e. recognizing specific activities in a stream of several sequential activities with unknown duration and arbitrary transitions between different classes of activities. A review on the current state of the art in this relatively new topic is given, followed by a discussion on future research directions.INDEX TERMS Radar applications, radar signal processing, continuous human activity recognition, activities of daily living.This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

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“…Human detection radar systems have been widely studied and have attracted attention with human identification and the detection of biological signals such as respiration and heartbeat. Accurate estimation of a person's location is also becoming important to improve the accuracy of these detections [1], [2], [3], [4], [5], [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Multi-Person Position Estimation Based on Correlation Between Received Signals Using MIMO FMCW Radar

et al. 2023

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By using Multiple-Input Multiple-Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar, a range-angle map can be obtained that displays the signal strength in two dimensions with respect to distance and angular directions. In this process, a threshold algorithm such as Constant False Alarm Rate (CFAR) is used to detect positions where the signal strength exceeds a certain threshold value, enabling position estimation of targets. Furthermore, a method has been proposed to use the curve length of the trajectory of the I/Q signal to emphasize the signal of the person's position on the range angle map. However, the conventional CFAR may cause false alarms when noise and clutter signals are strong. In this paper, we propose a new method for human location estimation using the MIMO FMCW radar. Comparing the reflected signals from people and clutter, we see that I/Q signal variations associated with human motion have little correlation with clutter from stationary objects or noise, and I/Q signal variations associated with clutter often have high correlation with signals at other positions. We focus on the fact that there are many positions where the clutter component signal has a high correlation, compared to the signal caused by a person. Using the correlation map that expresses the correlation between the received I/Q signals on the range-angle plane, we evaluated the characteristics of noise and clutter components from walls on the correlation map by standard deviation. As a result, we can remove strong noise and clutter components caused from near walls, thus improving the accuracy of object location estimation.

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Detection of Human Breathing in Non-Line-of-Sight Region by Using mmWave FMCW Radar

Cited by 25 publications

References 44 publications

Simulation and Implementation of Signal Processing for LFM Radar Using DSK 6713

Simulation and Implementation of Signal Processing for LFM Radar Using DSK 6713

A Survey on Radar-Based Continuous Human Activity Recognition

Multi-Person Position Estimation Based on Correlation Between Received Signals Using MIMO FMCW Radar

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