Rayleigh-based segmentation of ISAR images.

Inverse synthetic aperture radar (ISAR) provides a solution to increase the radar angular resolution by observing a moving target over time. The high-resolution ISAR image should undergo a segmentation step to get the target's point cloud data, which is then used for classification purposes. Existing segmentation algorithms seek an optimal threshold in an iterative manner, which adds to the complexity of ISAR and results in an increase in the processing time.

Automatic radar-based 2-D localization exploiting vital signs signatures.

In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths.

Improving the Accuracy of Spiking Neural Networks for Radar Gesture Recognition Through Preprocessing.

Event-based neural networks are currently being explored as efficient solutions for performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural networks coupled to adequate preprocessing must be investigated. Within this context, we demonstrate a 4-b-weight spiking neural network (SNN) for radar gesture recognition, achieving a state-of-the-art 93% accuracy within only four processing time steps while using only one convolutional layer and two fully connected layers.

A Direct Phase-Tracking Doppler Radar Using Wavelet Independent Component Analysis for Non-Contact Respiratory and Heart Rate Monitoring.

A continuous wave Doppler radar, operating as a phase-locked-loop in phase demodulator configuration, is proposed and in vivo demonstrated for noncontact vital signs monitoring. The radar architecture exhibits a unique precision in tracking the phase modulation caused by human cardiopulmonary activity from which heartbeat and respiration can simultaneously be extracted. The single mixer architecture is immune to the null point and does not require small-angle approximation conditions, which distinguishes it from pre-existing other approaches.

Frequency-Tracking CW Doppler Radar Solving Small-Angle Approximation and Null Point Issues in Non-Contact Vital Signs Monitoring.

A Doppler radar operating as a Phase-Locked-Loop (PLL) in frequency demodulator configuration is presented and discussed. The proposed radar presents a unique architecture, using a single channel mixer, and allows to detect contactless vital signs parameters while solving the null point issue and without requiring the small angle approximation condition. Spectral analysis, simulations, and experimental results are presented and detailed to demonstrate the feasibility and the operational principle of the proposed radar architecture.

Dual-polarization OFDM-OQAM for communications over optical fibers with coherent detection.

In order to improve the spectral efficiency of coherent optical communication systems, it has recently been proposed to make use of the orthogonal frequency-division multiplexing offset quadrature amplitude modulation (OFDM-OQAM). Multiple optical channels spaced in the frequency domain by the symbol rate can be transmitted orthogonally, even if each channel overlaps significantly in frequency with its two adjacent channels. The solutions proposed until now in the literature unfortunately only address a single polarization communication, and therefore do not benefit from the capacity gain reached when two polarizations are used to transmit independent information signals.