With the advancement of radio frequency (RF) assisted smart home technology, it is critical for the RF sensors deployed indoors to isolate the target of interest from unwanted clutter sources. This paper presents a novel method for suppressing both moving and stationary clutters in an indoor environment to localize stationary human subjects with a millimeter-wave frequency-modulated continuous-wave (FMCW) radar. The method derives its roots from the intrinsic high-pass filter (HPF) characteristic of the exponential moving average (EMA) algorithm, a preferred approach for background stationary clutter suppression. In this work, emphasis was laid on expanding the capability to detect and suppress unwanted moving clutter sources in the indoor environment along with stationary clutters, which has not been widely explored before. The proposed method removes motion artifacts so that the characteristic respiratory signal can be identified for human-aware localization. The paper provides experimental validation of the proposed method, wherein a 60-GHz FMCW radar with digital beamforming (DBF) capability was used to identify the 2-D location of a sitting human subject, with a moving window curtain in the background acting as a strong moving clutter source along with other stationary clutters. In addition, a lateral hand gesture recognition technique is presented, wherein the EMA algorithm was used to enhance the signature of the hand motion. The instantaneous position of the hand at the beginning and end of the gesture was determined to classify the gesture as a left-to-right or right-to-left hand swipe.

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Human Presence Sensing and Gesture Recognition for Smart Home Applications With Moving and Stationary Clutter Suppression Using a 60-GHz Digital Beamforming FMCW Radar

This work studies the feasibility of using backscatter-modulated tags to introduce false information into a signal received by a frequency-modulated continuous-wave (FMCW) radar. A proof-of-concept spoofing device was designed in the 24 GHz ISM band. The spoofing device was based on an amplifier connected between two antennas, and modulation was carried out by switching the amplifier bias. The use of an amplifier allowed us to increase the level of spoofing signal compared with other modulated backscattering methods. The simulated and experimental results show that our method has the ability to generate a pair of false targets at different ranges and velocities depending on the modulation frequency of the chosen tag, since sidebands appear due to this modulation. Countermeasures to detect the spoofing attack based on changes in the slope of the frequency sweep between frames are also proposed.

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Spoofing Attacks on FMCW Radars with Low-Cost Backscatter Tags

Visual tracking in complex scenes: A location fusion mechanism based on the combination of multiple visual cognition flows

This paper proposes a novel time-space dimension reduction method for millimeter-wave radar point-clouds on long-distance or large-field-of-view hand-gesture recognition. First, a two-dimensional antenna array is used to obtain radar point-clouds composed of range, Doppler, azimuth, elevation, and amplitude. The point-cloud time series are further reduced in dimensionality to reconstruct radar spectrums with less interference and better time-space continuity in the Range-Doppler-Azimuth-Elevation (RDAE) domain, and generate new spatial position spectrums after transforming to the three-dimensional cartesian coordinate system, which are superior to radar spectrums in the RDAE domain in terms of space invariance. Then a spatial position alignment method is proposed to improve the spatial consistency of multi-position dataset. Finally, a multi-channel convolutional neural network is designed for multi-position hand-gesture recognition. Experimental results show that the proposed method can solve the problems of poor space invariance in the RDAE domain and poor generalization performance for different spatial positions and different users in existing methods. For hand-gesture recognition within a long distance of 3 meters and a large field-of-view of 60 degrees, the average classification accuracies of 5 waving hand-gestures collected at multiple positions for trained user A, non-trained user B, and non-trained user C can reach 99.7%, 91.1%, and 87.1%, respectively.

Time-Space Dimension Reduction of Millimeter-Wave Radar Point-Clouds for Smart-Home Hand-Gesture Recognition

Portable, low-cost, microwave radars have attracted researchers’ attention for being an alternative noncontact solution for structural condition monitoring. In addition, by leveraging their capability of providing the target velocity information, the radar-based remote monitoring of complex rotating structures can also be accomplished. Modern radar systems are compact, able to be easily integrated in sensor networks, and can deliver high accuracy measurements. This paper reviews the recent technical advances in low-cost Doppler radar systems for phase-demodulated displacement measurements and time-Doppler analysis for structural health information, including digital signal processing and emerging applications related to radar sensor networks.

A Review on Low-Cost Microwave Doppler Radar Systems for Structural Health Monitoring

In this article, fully integrated binary phase shift keying (BPSK) tags are presented to work in conjunction with narrowband frequency-shift keying (FSK) radar for concurrent multitarget range tracking and vital signs sensing. Without the employment of any radio frequency (RF) mixer, the developed BPSK tag introduces a frequency offset by generating periodic phase shifts to the radar carrier frequencies with optimized power level. The theory of BPSK tag-based range tracking and vital signs sensing in conjunction with FSK radar signal is developed. An impedance-modulated 24-GHz tag architecture without any active RF components is proposed and its implementation and characterization are presented. The system performance is evaluated in the following residential indoor scenarios: single tag ranging, concurrent multiple tags and an untagged human target detection, and multiple tagged human targets tracking. Promising ranging performance demonstrates the potential for the proposed system to be adopted in various indoor tracking applications.

24-GHz Impedance-Modulated BPSK Tags for Range Tracking and Vital Signs Sensing of Multiple Targets Using an FSK Radar

This article presents a novel spoofing device capable of injecting false target information into a frequency-modulated continuous-wave (FMCW) radar. The spoofing device uses a radio frequency (RF) single-sideband (SSB) mixer to introduce a frequency shift to the incoming RF signal transmitted by the victim radar and retransmits the modulated RF signal. The modulated RF signal resembles a false target. Upon down-conversion on the receiver chain of the victim radar, the modulated RF signal creates an illusion of a real target in the radar signal processing system. The frequency shift can be adjusted to vary the range of the spoofed target. The theory of the spoofing mechanism was developed, and a 5.8 GHz prototype was built for experimental validation. Experimental results demonstrate the ability of the proposed spoofing device to inject a false target at any arbitrary range. A hybrid-chirp FMCW approach was proposed and verified as a countermeasure to distinguish a real target from a spoofed target to mitigate the RF-spoofing attack.

A Frequency-Domain Spoofing Attack on FMCW Radars and Its Mitigation Technique Based on a Hybrid-Chirp Waveform

This paper presents a portable 24-GHz multiple-input multiple-output (MIMO) radar with 16 transmit (Tx) channels and 16 receive (Rx) channels. The radar is intended for short-range localization and three-dimensional (3-D) imaging by detecting the ranges, azimuth angles, and zenith angles of targets in front of the radar. The radar is capable of two-dimensional (2-D) beamforming achieved using a non-uniformly spaced planar array. A prototype of this 16×16 radar has been built to demonstrate its short-range localization capability.

Design and Calibration of a Portable 24-GHz 3-D MIMO FMCW Radar with a Non-uniformly Spaced Array and RF Front-End Coexisting on the Same PCB Layer

This paper presents the concept of a radio frequency (RF) compressed sensing radar for indoor localization. A digital beamforming architecture for RF physical layer compressed sensing is discussed. Compressed sensing can reconstruct an under-sampled signal provided it is sparse in nature. A pseudo random multi-beam radiation pattern will be used to scan the target frame. The spatial sparsity in the target frame helps in recovering the entire frame using less number of scans compared to the conventional indoor localization system.

Prateek Nallabolu

Papers

Human Presence Sensing and Gesture Recognition for Smart Home Applications With Moving and Stationary Clutter Suppression Using a 60-GHz Digital Beamforming FMCW Radar

24-GHz Impedance-Modulated BPSK Tags for Range Tracking and Vital Signs Sensing of Multiple Targets Using an FSK Radar

A Frequency-Domain Spoofing Attack on FMCW Radars and Its Mitigation Technique Based on a Hybrid-Chirp Waveform

Design and Calibration of a Portable 24-GHz 3-D MIMO FMCW Radar with a Non-uniformly Spaced Array and RF Front-End Coexisting on the Same PCB Layer

RF Compressed Sensing Radar Based on Digital Beamforming for Localization and IoT Applications