In this work, the authors present results for classification of different classes of targets (car, single and multiple people, bicycle) using automotive radar data and different neural networks. A fast implementation of radar algorithms for detection, tracking, and micro-Doppler extraction is proposed in conjunction with the automotive radar transceiver TEF810X and microcontroller unit SR32R274 manufactured by NXP Semiconductors. Three different types of neural networks are considered, namely a classic convolutional network, a residual network, and a combination of convolutional and recurrent network, for different classification problems across the four classes of targets recorded. Considerable accuracy (close to 100% in some cases) and low latency of the radar pre-processing prior to classification (∼0.55 s to produce a 0.5 s long spectrogram) are demonstrated in this study, and possible shortcomings and outstanding issues are discussed.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rsn.2018.0103

Practical classification of different moving targets using automotive radar and deep neural networks

Background Recently, there has been a dramatic change in the field of terahertz (THz) technology. The recent advancements in the THz radiation sector considering generation, manipulation and detection have brought revolution in this field, which enable the integration of THz sensing systems into real-world. The THz technology presents detection techniques and various issues, while providing significant opportunities for sensing food and water contamination detection. Scope and approach Many researchers around the world have exploited the potential of invaluable new applications of THz sensing ranging from surveillance, healthcare and recently for food and water contamination detection. The microbial pollution in water and food is one the crucial issues with regard to the sanitary state for drinking water and daily consumption of food. To address this risk, the detection of microbial contamination is of utmost importance, since the consumption of insanitary or unhygienic food can lead to catastrophic illness. Key findings and conclusions This paper presents a first-time review of the open literature covering the advances in the THz sensing for microbiological contamination of food and water, in addition to state-of-the-art in network architectures, applications and recent industrial developments. With unique superiority, the THz non-destructive detection technology in food inspection and water contamination detection is emerging as a new area of study. With the great progress, some important challenges and future research directions are presented within the field.

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State-of-the-art in terahertz sensing for food and water security – A comprehensive review

Because it is sensitive to fluctuations occurring over femtoseconds to picoseconds, gigahertz-to-terahertz dielectric relaxation spectroscopy can provide a valuable window into water's most rapid intermolecular motions. In response, we have built a vector network analyzer dielectric spectrometer capable of measuring absorbance and index of refraction in this frequency regime with unprecedented precision. Using this to determine the complex dielectric response of water and aqueous salt solutions from 5.9 GHz to 1.12 THz (which we provide in the SI), we have obtained strong new constraints on theories of water's collective dynamics. For example, while the salt-dependencies we observe for water's two slower relaxations (8 and 1 ps) are easily reconciled with suggestions that they arise due to rotations of fully and partially hydrogen bonded molecules, respectively, the salt-dependence of the fastest relaxation (180 fs) appears difficult to reconcile with its prior assignment to liberations of single hydrogen bonds.

High-precision gigahertz-to-terahertz spectroscopy of aqueous salt solutions as a probe of the femtosecond-to-picosecond dynamics of liquid water

Wave attenuation through rain with different rainfall rates at millimeter wave ( $f = 77$ GHz) and low-terahertz (Low-THz) ( $f = 300$ GHz) frequencies is studied in this article. Rain has pronounced impacts on electromagnetic wave propagation and one of the well-known effects is attenuation of the transmitted wave. Attenuation at both frequencies and hydrometeor properties [rainfall rate and drop size distribution (DSD)] are measured simultaneously. The measured DSD is fit with gamma and Weibull distributions and is also compared to the frequently used distribution Marshall and Palmer (MP) model; Weibull is shown to be a better fit to the measured DSDs. Theoretical prediction of attenuation as a function of rainfall rate (up to about 20 mm/h) is determined using Mie scattering theory, and the fit gamma and Weibull, and MP distribution models; as well as using the International Telecommunications Union Radiocommunication Sector (ITU-R) recommendation. The calculations are evaluated by comparing them to the experiment. The measured results at 77 GHz best agree with the ITU-R recommendation whereas at 300 GHz, the calculation based on Mie scattering and the Weibull distribution exhibits the best fit to the measured data. The measured data that exceed the theoretical prediction are analyzed and interpreted based on their corresponding observed drop size properties, for the first time.

Rain Attenuation at Millimeter Wave and Low-THz Frequencies

We present and discuss the case for full waveform pixel and image acquisition and processing to enable LiDAR sensors to penetrate and reconstruct 3D surface maps through obscuring media. To that end, we review work on signal propagation, on scanning and arrayed sensors, on signal processing strategies for independent pixels and employing spatial context, on reducing complexity and accelerating processing by sensor design, algorithmic changes, compressed sensing, and parallel processing. We report several experimental studies on LiDAR imaging through complex media, and how these can inform the automotive LiDAR scenario. We conclude with a discussion of future development and potential for full waveform LiDAR (FWL).

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Full Waveform LiDAR for Adverse Weather Conditions

This paper is concerned with modelling of the transmissivity of Low-Terahertz waves through automotive bumper and headlight cover material. This work is part of wider comprehensive studies on the potential for the use higher frequency bands for future automotive sensors. Theoretical models for transmissivity prediction are described, the methodology of experimentation is discussed and experimental results are presented. The theoretical models of reflection and transmission of different base materials which are covered by different layers of paint are based on Fresnel theory, and the phenomena caused by the half wavelength thickness of the medium is analyzed mathematically. The experimental verification of the models in this paper have been undertaken at 300 GHz and 670 GHz, using 77 GHz as a reference frequency.

Modeling and Experiment Verification of Transmissivity of Low-THz Radar Signal Through Vehicle Infrastructure

Experimental measurement results of automotive radar signal attenuation during various intensities of snowfall at the current automotive radar frequency (77 GHz) and low-terahertz (THz) (100-300 GHz) frequencies are presented and compared in this study. The attenuation is characterised by measuring the ratio of the received power from a reference target through snow precipitation of various intensities and through the same path with no precipitation. Statistical analysis of the attenuation is presented. Higher attenuation is measured at a higher frequency, and also attenuation increases as snowfall rate and liquid water content in snowflakes increases. This study is fundamentally important to investigate the effect of adverse weather conditions on low-THz radar performance in comparison with the current automotive radars operating in the traditional mm-wave band. In addition, the effects of low-THz wave attenuation and scattering due to typical contaminants formed on the radome of automotive radars and reflection from common objects on the road are presented.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rsn.2018.5644

Experimental study on low-THz automotive radar signal attenuation during snowfall

In this paper, signal reduction due to the presence of water content formed on a radome has been studied at low-THz frequencies. The effect of obscurants on signal reduction has been characterized by measuring the ratio of reflected signals from a reference target through the radome, with contaminant and without contaminant. All the measurements have been compared to theoretical models, demonstrating a reasonable agreement. Water is the most common obscurant in outdoor applications and the main cause of performance deterioration in rainy, snowy, and foggy weather. This paper concentrates on the attenuation caused by different forms of distribution of water as a radome contaminant. Both a thin uniform layer of water and randomly distributed water droplets are studied at 150 and 300 GHz. The results show strong signal reduction due to the presence of uniform thickness of water and higher signal reduction with increasing frequency. However, the measured transmissivity through distributed water droplets, which occur in practice due to the surface tension of water, shows lower transmission loss at the shorter wavelength, due to transmission through the distribution of gaps between droplets.

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Low-THz Transmission Through Water-Containing Contaminants on Antenna Radome

Low-terahertz (THz) (above 150 GHz) radar sensing is one of the promising technologies to provide safe navigation for autonomous cars due to its expected high-resolution imaging capability. It is anticipated that for robust operation at high levels of autonomy the sensor suite should provide a fusion of video and radar data and its efficiency depends on radar ability to deliver a resolution high enough to be compatible with that of the optical image. Performance of low-THz radar, capable to deliver required resolution, is considered in this study, with the focus on reflectivities of pedestrians at frequencies within the low-THz region – 150 and 300 GHz. Backscatter returns are collected in a controlled environment at a number of frequency bands and at different aspect angles. Measurement methodology is presented and several indicators of reflectivities are calculated. Results are compared with values of radar cross-section reported for current automotive frequency standards 24 and 77 GHz. The effect of clothing on reflectivities is also considered in this study.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rsn.2018.5016

Fatemeh Norouzian

Papers

Rain Attenuation at Millimeter Wave and Low-THz Frequencies

Modeling and Experiment Verification of Transmissivity of Low-THz Radar Signal Through Vehicle Infrastructure

Experimental study on low-THz automotive radar signal attenuation during snowfall

Low-THz Transmission Through Water-Containing Contaminants on Antenna Radome

Radar cross-section of pedestrians in the low-THz band