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

The millimeter waves have large available bandwidth and thus gigabit throughput can be easily achieved for future wireless communication systems. The frequency band has been identified as potentially suitable frequency band for IMT (International Mobile Telecommunications) systems. In this paper, consideration ECC and Huawei relevant paper, the coexistence interference of 71-78 GHz-band international mobile telecommunications (IMT) and automotive radar is analyzed based on actual geographical and ITU-R system characteristic. Specifically, the interferences of IMT system base stations (BS) and users (UE) to automotive radar are studied, considering high frequency band radio propagation clutter loss. This paper presents the Monte Carlo results in terms of the level of compatibility interference power vs. the distances between IMT and automotive radar in the straight trajectory by using Visualyse V7.9 simulation tool. The results show that in some case the IMT BS operating in the band 71-76 GHz may be well compatible with the automotive radar, the interference power value is mainly under protection criterion value. The provided results are useful for design of future 71/80 GHz IMT-2020 (5G) wireless communications systems and automotive radar system.

Due to the increasing number of vehicles equipped with millimeter wave (mmWave) radars, interference among automotive radars is becoming a major issue. This paper explores the automotive radar interference in both two-lane and multi-lane scenarios using stochastic geometry. We derive closed-form expressions for mean and variance of interference power considering directional antenna with constant and Gaussian decaying gains. In view of the sensitivity of mmWave radar signals to the blockages, we propose a blockage model including partially and completely blocking, and then calculate the effective number of the interferers. By means of modeling randomness for interferers and blockages as Poisson point process, we characterize the statistics of radar interference under different conditions. We further utilize the interference characterization to estimate the successful ranging probability of automotive radars. These theoretical analyses are verified by using Monte Carlo simulations. The results show that the increasing interfering density and ranging distance largely degrade the radar detection performance, whereas the interference levels decrease as blockage intensity increases.

Sensitivity and performance of homodyne radar are notably improved if the phase noise terms of transmit and receive signals are correlated and canceled out by the receiver. However, in a bistatic setup with separate oscillators, this correlation is inherently not given. To achieve a good carrier phase and phase noise coherency, it is required to transmit a radio frequency (RF) reference, e.g., by using high-quality RF cables, optical fibers, or wireless point-to-point links. All these options are complex, costly, and prone to distortions and signal delay variations. Sharing a clock signal is also barely helpful since even small distortions of this reference are converted to notable uncorrelated phase noise in the radar signal synthesizers. In this article, a novel full-duplex system concept and signal processing scheme is presented that solves the above-mentioned problems completely. This concept allows for coherent measurements within a bistatic radar setup, even if the two radar stations are only loosely coupled employing a simple clock-rate adjustment. By theory and experimental results with bistatic frequency-modulated continuous-wave radar, it is shown that our concept allows for bistatic measurements with the same sensitivity and performance that is usually only known from homodyne radar systems. To the authors' best knowledge, this is the first time that phase noise coherent measurements in a bistatic multiple-input multiple-output radar setup are shown. This concept paves the way for advanced netted radar setups, e.g., in automotive radar and applications with large apertures or baselines or multiperspective coherent tomographic measurements.

In this study, the authors propose a periodic clutter suppression method in iron road structures for automotive radar systems. Specific road structures made of iron such as tunnels, soundproof walls, and guardrails have periodic steel frames that generate unwanted reflected signals called radar clutter. This clutter degrades the detection performance of an automotive radar and leads to misdetection of targets. Therefore, efficient signal processing is required to mitigate the adverse effect of clutter within those iron structures. Since the spacings between steel frames are uniform, beat frequencies corresponding to them also appear at regular intervals. This phenomenon is maintained in each radar scan when a vehicle travels in the iron structures. Thus, they suggest an effective periodic clutter suppression method using the relationship between adjacent radar scans. Their proposed clutter suppression scheme was applied to radar signals obtained from the iron road structures and successfully suppressed the periodic clutter.

Radar communications (RadCom) is a spectrally efficient way for removing automotive radar interference and thereby enhancing reliable radar sensing, via a single hardware for both radar and communications. When interference coordination does not use all the RadCom resources, opportunities for communicating additional data arise. We propose a new communication protocol, termed RadNet (for radar network), which forms a vehicular ad-hoc multi-hop network by automotive radars in a distributed manner. Simulation results obtained for high-way use cases show that RadNet can enable several Mbps data links without degrading the radar performance.

On attenuation of free and forced waves in an infinitely long visco-elastic layer of a constant thickness

This paper presents a 75–90 GHz down-conversion mixer applied in automotive radar, which is characterized with high linearity, low local oscillator (LO) drive as well as high conversion gain (CG) using TSMC 65-nm CMOS general-purpose technology. The good linearity and isolation of mixer are required for automotive radar to cover short-middle-far range detection. The mixer includes an enhanced double-balanced Gilbert-cell core with series peaking transmission line and source degeneration technique for improving linearity and CG, two on-chip baluns and intermediate frequency (IF) buffer for IF test. Besides, to make the design more accurate and efficient, the modeling and design of millimeter-wave (mm-wave) passive devices are introduced. The mixer consumes 12 mW under 1.5 V. The input 1 dB compression point (P1dB) is 2.5 dBm as well as IIP3 of 13.2 dBm at 80 GHz. High performances are achieved with the CG of 5 dB at 76 GHz with LO power of 0 dBm for frequencies of 75–90 GHz which covers the application of automotive radar frequency band (76–81 GHz) and LO-RF isolation of 33–37 dB for frequencies of 60–90 GHz. The area of the mixer is 0.14 mm2, with PADs included.

Automotive radar sensors play a vital role in the development of autonomous driving due to their ability to detect objects even under adverse conditions [1] . Besides that, radar sensors offer long range capability and compact size, which enables the implementation in tight spaces. The environmental sensing task in autonomous vehicles must be validated due the severity of an operational failure that endangers human life. Carrying out these validation tests in the field however, presents a risk to other traffic participants and involves a great effort since distances in the order of several hundred million kilometer have to be covered to ensure the proper functioning of the system [2] . Also, these test are not repeatable. For this reason, a so-called Vehicle-in-the-Loop (ViL) approach is considered using a end-of-line vehicle placed on a steerable chassis dynamometer with the ability to simulate real world test scenarios. Such Radar Target Simulators (RTS) are capable of performing end-of-line, over-the-air validation tests by looping back a received signal and afterwards modified radar signal. It is essential, that these simulated targets are very close to reality and can also be compared to test drive data. However, this requires that all involved phenomena are investigated and implemented correctly. The radar signal is emitted from the sensor, travels through the radar radio channel, is reflected at an object, and travels back through the radio channel to the receiver, which in the case of radar is typically at the same location as the transmitter. Wave propagation must therefore take into account multiple reflections and scattering from objects in addition to free space propagation. To take the scattering or the backscattering into account, the so-called RCS pattern is usually used. However, since modern automotive radars are capable of resolving individual scattering centers well in angle and distance, considering the target as a point scatterer is far from sufficient. Therefore, a measurement system is presented that is able to measure road users with high resolution. This is done by using a mmW FMCW Radar Sensor working in the frequency range from 76-81 GHz which is equipped with a highly-directive lens antenna. Several traffic participants like cars, bikes, motor bikes and vulnerable road users are measured in detail. Also, measurements are compared to different full wave simulations. However, the results of these measurements cannot be implemented into a Radar Target Simulators, since the number of antennas that are necessary to generate the scattering points is limited, e.g. four antennas [3] . For this reason, the measured scattering points must be combined into relevant scattering clusters, which can then also be simulated with the limited number of antennas of the radar target simulator. The used radar target simulators in this approach is capable of generating echoes by using eight antennas. Each of the scattering clusters is consequently implanted in the wave propagation by its specific RCS pattern.

This paper describes the electromagnetic wave (EM) attenuation by concrete blocks focusing on the frequency range 1.70 – 1.88 GHz and 3.40 – 3.80 GHz. The attenuation calculation of concrete was made according to ITU recommendation ITU-R P.2040-1 (07/2015) for conducting dielectric. Also, the attenuation calculation was made using simulated values of S 11 and S 21 parameters. These two sets of computationally derived data were compared with each other, and the differences were not significant. The values of EM wave attenuation during propagation through concrete were compared with the values from the available literature and the deviations are also minor. 5G systems use higher frequencies and the tested concrete materials shield the 5G signals better than 4G signals. The results of this research can be used in the building walls with high attenuation for 4G and 5G communication systems.

Hysteretic Elastic Wave Velocity and Attenuation in Partially Saturated Sandstone by CO2 and Brine: Evidenced by an Experimental Study with X-ray CT

Pedestrian Collision Mitigation Systems (PCMS) are in the market for a few years. Due to continuously evolving Euro NCAP regulations their presence will rapidly increase. Visual sensors, already capable of pedestrian classification, provide functional benefits because system responses can be better adapted to expected pedestrian's behavior. Nevertheless their performance will suffer under adverse environmental conditions like darkness, fog, rain or backlight. Even in such situations the performance of radar sensors is not significantly deteriorated. Enabling classification capability for radar-based systems will increase road safety further and will lower PCMS's overall costs. In this paper a multi-reflection-point pedestrian target model based on motion analysis is presented. Together with an appropriate sensor model, pedestrian radar signal responses can be provided for a wide range of relevant accident scenarios, without risk for the health of test persons. Besides determination of human classification features, the model provides identification of the limits in classical radar signal processing. Beyond these borderlines it offers the opportunity to evaluate parametric spectral analysis methods.

High quality perception is essential for autonomous driving (AD) systems. To reach the accuracy and robustness that are required by such systems, several types of sensors must be combined. Currently, mostly cameras and laser scanners (lidar) are deployed to build a representation of the world around the vehicle. While radar sensors have been used for a long time in the automotive industry, they are still under-used for AD despite their appealing characteristics (notably, their ability to measure the relative speed of obstacles and to operate even in adverse weather conditions). To a large extent, this situation is due to the relative lack of automotive datasets with real radar signals that are both raw and annotated. In this work, we introduce CARRADA, a dataset of synchronized camera and radar recordings with range-angle-Doppler annotations. We also present a semi-automatic annotation approach, which was used to annotate the dataset, and a radar semantic segmentation baseline, which we evaluate on several metrics.

The successful implementation of autonomous driving in an urban setting depends on the ability of the environment perception system to correctly classify vulnerable road users such as pedestrians and bicyclists in dense, complex scenarios. Self-driving vehicles include sensor systems such as cameras, lidars, and radars to enable decision making. Among these systems, radars are particularly relevant due to their operational robustness under adverse weather and night light conditions. Classification of pedestrian and car in urban settings using automotive radar has been widely investigated, suggesting that micro-Doppler signatures are useful for target discrimination. Our objective is to analyze and study the micro-Doppler signature of bicyclists approaching a vehicle from different directions in order to establish the basis of a classification criterion to distinguish bicycles from other targets including clutter. The micro-Doppler signature is obtained by grouping individual reflecting points using a clustering algorithm and observing the evolution of all the points belonging to an object in the Doppler domain over time. A comparison is then made with simulated data that uses a kinematic model of bicyclists’ movement. The suitability of the micro-Doppler bicyclist signature as a classification feature is determined by comparing it to those belonging to cars and pedestrians approaching the automotive radar system.

We present a novel approach which is helpful in building an inexpensive security or surveillance system for various applications. The system consists of a radar network that creates a virtual fence or barrier that is invisible, and in case of intrusion it will give an alarm, determine the location of a target and provide the target's relative velocity information. Our approach is a combination of continuous sensor measurements by commercially available automotive radar, specific network layout and advanced post-processing techniques. We use open source software and hardware to reduce the total cost of the system. The proposed network topology including radar coverage area is novel and similar to a half-fishbone shape, however the main focus of this paper is on creating a prototype of the radar network node. To get a control over the resolution of range measurements, the analysis of several post-processing algorithms for target detection was carried out. Another feature of our approach is an implementation of perceptual (robust) hash algorithm for storage of current signal ‘image’ in memory and comparison of the signal and ‘no-intrusion’ signal. During the work, applied software tool was created. It significantly simplifies the data acquisition and analysis. Extensive experimental measurements confirm the validity of the approach, show the performance of the radar and reveal some directions for future improvements.

In this paper, we developed an integrated mid-range automotive radar system with both blind spot detection (BSD) and lane change assistance (LCA) functions. Integrated automotive radar extends the maximum detection range to 80m with an update time that is within 50ms. By means of ROI preprocessing technique, the computation load of radar signal processing was improved. In order to evaluate the detection performance considering an actual driving environment, radar performance evaluations were conducted in various driving scenarios at an automotive proving ground.