scholarly journals Compressed Sensing for THz FMCW Radar 3D Imaging

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Shanshan Gu ◽  
Guangrong Xi ◽  
Lingyu Ge ◽  
Zhong Yang ◽  
Yizhi Wang ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
3D Imaging ◽  
Continuous Wave ◽  
Imaging System ◽  
Measurement Data ◽  
Radar Signal ◽  
Data Reconstruction ◽  
Signal Model ◽  
Fmcw Radar ◽  
Range Migration

A terahertz (THz) frequency-modulated continuous wave (FMCW) imaging radar system is developed for high-resolution 3D imaging recently. Aiming at the problems of long data acquisition periods and large sample sizes for the developed imaging system, an algorithm based on compressed sensing is proposed for THz FMCW radar 3D imaging in this paper. Firstly, the FMCW radar signal model is built, and the conventional range migration algorithm is introduced for THz FMCW radar imaging. Then, compressed sensing is extended for THz FMCW radar 3D imaging, and the Newton smooth L0-norm (NSL0) algorithm is presented for sparse measurement data reconstruction. Both simulation and measurement experiments demonstrate the feasibility of reconstructing THz images from measurements even at the sparsity rate of 20%.

scholarly journals FPGA Implementation of an Efficient FFT Processor for FMCW Radar Signal Processing

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6443
Author(s):  
Jinmoo Heo ◽  
Yongchul Jung ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Signal Processing ◽  
Detection Rate ◽  
Continuous Wave ◽  
Vital Signs ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Fmcw Radar ◽  
Design And Implementation ◽  
Fft Processor ◽  
Point Operator

This paper presents the design and implementation results of an efficient fast Fourier transform (FFT) processor for frequency-modulated continuous wave (FMCW) radar signal processing. The proposed FFT processor is designed with a memory-based FFT architecture and supports variable lengths from 64 to 4096. Moreover, it is designed with a floating-point operator to prevent the performance degradation of fixed-point operators. FMCW radar signal processing requires windowing operations to increase the target detection rate by reducing clutter side lobes, magnitude calculation operations based on the FFT results to detect the target, and accumulation operations to improve the detection performance of the target. In addition, in some applications such as the measurement of vital signs, the phase of the FFT result has to be calculated. In general, only the FFT is implemented in the hardware, and the other FMCW radar signal processing is performed in the software. The proposed FFT processor implements not only the FFT, but also windowing, accumulation, and magnitude/phase calculations in the hardware. Therefore, compared with a processor implementing only the FFT, the proposed FFT processor uses 1.69 times the hardware resources but achieves an execution time 7.32 times shorter.

scholarly journals Asynchronous electric field visualization using an integrated multichannel electro-optic probe

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shintaro Hisatake ◽  
Junpei Kamada ◽  
Yuya Asano ◽  
Hirohisa Uchida ◽  
Makoto Tojo ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Near Field ◽  
Horn Antenna ◽  
Optimal Placement ◽  
Radar Signal ◽  
Radiation Patterns ◽  
Practical Applications ◽  
Fmcw Radar ◽  
Realistic Situation ◽  
Reference Probe

Abstract The higher the frequency, the more complex the scattering, diffraction, multiple reflection, and interference that occur in practical applications such as radar-installed vehicles and transmitter-installed mobile modules, etc. Near-field measurement in “real situations” is important for not only investigating the origin of unpredictable field distortions but also maximizing the system performance by optimal placement of antennas, modules, etc. Here, as an alternative to the previous vector-network-analyzer-based measurement, we propose a new asynchronous approach that visualizes the amplitude and phase distributions of electric near-fields three-dimensionally without placing a reference probe at a fixed point or plugging a cable to the RF source to be measured. We demonstrate the visualization of a frequency-modulated continuous wave (FMCW) signal (24 GHz ± 40 MHz, modulation cycle: 2.5 ms), and show that the measured radiation patterns of a standard horn antenna agree well with the simulation results. We also demonstrate a proof-of-concept experiment that imitates a realistic situation of a bumper installed vehicle to show how the bumper alters the radiation patterns of the FMCW radar signal. The technique is based on photonics and enables measuring in the microwave to millimeter-wave range.

Semi-Physical Simulation System for FMCW Radar

2011 ◽  
Vol 135-136 ◽  
pp. 886-892
Author(s):  
Wen Hui Chen ◽  
Xin Xi Meng ◽  
Xiao Min Liu
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Physical Simulation ◽  
Continuous Wave ◽  
Low Cost ◽  
Simulation System ◽  
Radar Signal ◽  
Low Power Consumption ◽  
Fmcw Radar ◽  
Data Process

In order to process and analyze the signal of frequency modulated continuous wave (FMCW) radar, a radar semi-physical simulation(RSPS) system based on STM32F103VE6 chip is designed in this paper. By designing the hardware and software of system, the RSPS system can process the radar signal, detect the target, verify the data process algorithm and display the result on TFT-LCD screen. In addition, the collected data can be uploaded to PC by RS-232 interfaces which improves the reliability, stability and practicability of system. The waveform and spectrum maps are utilized to show the feasibility of RSPS system in analysing FMCW radar signal. Experimental results show that this system has many advantages, such as multifunction, low power consumption and low cost.

scholarly journals Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6505
Author(s):  
Emmi Turppa ◽  
Juha M. Kortelainen ◽  
Oleg Antropov ◽  
Tero Kiuru
Keyword(s):  
Heart Rate ◽  
Remote Monitoring ◽  
Vital Sign ◽  
Continuous Wave ◽  
Real Life ◽  
Vital Signs ◽  
Absolute Error ◽  
Physical Contact ◽  
Radar Signal ◽  
Fmcw Radar

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.

scholarly journals Automotive Frequency Modulated Continuous Wave Radar Interference Reduction Using Per-Vehicle Chirp Sequences

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2831 ◽  
Author(s):  
Youn-Sik Son ◽  
Hyuk-Kee Sung ◽  
Seo Heo
Keyword(s):  
Continuous Wave ◽  
Signal Interference ◽  
Radar Signal ◽  
Driver Assistance ◽  
Interference Reduction ◽  
Fmcw Radar ◽  
Radar Sensors ◽  
Vehicle To Vehicle ◽  
Radar Systems ◽  
Wave Radar

Recently, many automobiles adopt radar sensors to support advanced driver assistance system (ADAS) functions. As the number of vehicles with radar systems increases the probability of radar signal interference and the accompanying ghost target problems become serious. In this paper, we propose a novel algorithm where we deploy per-vehicle chirp sequence in a frequency modulated continuous wave (FMCW) radar to mitigate the vehicle-to-vehicle radar interference. We devise a chirp sequence set so that the slope of each vehicle’s chirp sequence does not overlap within the set. By assigning one of the chirp sequences to each vehicle, we mitigate the interference from the radar signals transmitted by the neighboring vehicles. We confirm the performance of the proposed method stochastically by computer simulation. The simulation results show that the detection and false alarm performance is improved significantly by the proposed method.

scholarly journals Multi-Input Deep Learning Based FMCW Radar Signal Classification

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1144
Author(s):  
Daewoong Cha ◽  
Sohee Jeong ◽  
Minwoo Yoo ◽  
Jiyong Oh ◽  
Dongseog Han
Keyword(s):  
Deep Learning ◽  
Point Cloud ◽  
Continuous Wave ◽  
Autonomous Driving ◽  
Radar Data ◽  
Classification Performance ◽  
Radar Signal ◽  
Fmcw Radar ◽  
Input Structure ◽  
Single Input

In autonomous driving vehicles, the emergency braking system uses lidar or radar sensors to recognize the surrounding environment and prevent accidents. The conventional classifiers based on radar data using deep learning are single input structures using range–Doppler maps or micro-Doppler. Deep learning with a single input structure has limitations in improving classification performance. In this paper, we propose a multi-input classifier based on convolutional neural network (CNN) to reduce the amount of computation and improve the classification performance using the frequency modulated continuous wave (FMCW) radar. The proposed multi-input deep learning structure is a CNN-based structure using a distance Doppler map and a point cloud map as multiple inputs. The classification accuracy with the range–Doppler map or the point cloud map is 85% and 92%, respectively. It has been improved to 96% with both maps.

scholarly journals Time-Varying Vibration Compensation Based on Segmented Interference for Triangular FMCW LiDAR Signals

2021 ◽  
Vol 13 (19) ◽  
pp. 3803
Author(s):  
Rongrong Wang ◽  
Bingnan Wang ◽  
Yachao Wang ◽  
Wei Li ◽  
Zhongbin Wang ◽  
...  
Keyword(s):  
3D Imaging ◽  
Continuous Wave ◽  
Imaging System ◽  
Vibration Velocity ◽  
Time Varying ◽  
Traditional Methods ◽  
Numerical Tests ◽  
Single Period ◽  
Vibration Compensation ◽  
The Impact

Frequency modulation continuous wave (FMCW) light detection and ranging (LiDAR) 3D imaging system may suffer from time-varying vibrations which will affect the accuracy of ranging and imaging of a target. The system uses only a single-period FMCW LiDAR signal to measure the range of each spot; however, traditional methods may not work well to compensate for the time-varying vibrations in a single period because they generally assume the vibration velocity is constant. To solve this problem, we propose a time-varying vibration compensation method based on segmented interference. We first derive the impact of time-varying vibrations on the range measurement of the FMCW LiDAR system, in which we divide the time-varying vibration errors into primary errors caused by the vibrations with a constant velocity and quadratic errors. Second, we estimate the coefficients of quadratic vibration errors by using a segmented interference method and build a quadratic compensation filter to eliminate the quadratic vibration errors from the original signals. Finally, we use the symmetrical relations of signals in a triangular FMCW period to estimate the vibration velocity and establish a primary compensation filter to eliminate the primary vibration errors. Numerical tests verify the applicability of this method in eliminating time-varying vibration errors with only a one-period triangular FMCW signal and its superiority over traditional methods.

scholarly journals Comparison of digital beamforming algorithms for 3-D terahertz imaging with sparse multistatic line arrays

2017 ◽  
Vol 15 ◽  
pp. 283-292 ◽  
Author(s):  
Bessem Baccouche ◽  
Patrick Agostini ◽  
Falco Schneider ◽  
Wolfgang Sauer-Greff ◽  
Ralph Urbansky ◽  
...  
Keyword(s):  
Continuous Wave ◽  
Imaging System ◽  
Near Field ◽  
Terahertz Imaging ◽  
Projection Algorithm ◽  
Back Projection ◽  
Digital Beamforming ◽  
Linear Movement ◽  
Range Migration ◽  
Continuous Wave Signal

Abstract. In this contribution we compare the back-projection algorithm with our recently developed modified range migration algorithm for 3-D terahertz imaging using sparse multistatic line arrays. A 2-D planar sampling scheme is generated using the array's aperture in combination with an orthogonal synthetic aperture obtained through linear movement of the object under test. A stepped frequency continuous wave signal modulation is used for range focusing. Comparisons of the focusing quality show that results using the modified range migration algorithm reflect these of the back-projection algorithm except for some degradation along the array's axis due to the operation in the array's near-field. Nevertheless the highest computational efficiency is obtained from the modified range migration algorithm, which is better than the numerically optimized version of the back-projection algorithm. Measurements have been performed by using an imaging system operating in the W frequency band to verify the theoretical results.

scholarly journals Dynamic Hand Gesture Recognition in In-Vehicle Environment Based on FMCW Radar and Transformer

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6368
Author(s):  
Lianqing Zheng ◽  
Jie Bai ◽  
Xichan Zhu ◽  
Libo Huang ◽  
Chewu Shan ◽  
...  
Keyword(s):  
Gesture Recognition ◽  
Continuous Wave ◽  
Region Of Interest ◽  
Recognition System ◽  
Hand Gesture Recognition ◽  
Radar Signal ◽  
Hand Gesture ◽  
Feature Maps ◽  
Fmcw Radar ◽  
Background Removal

Hand gesture recognition technology plays an important role in human-computer interaction and in-vehicle entertainment. Under in-vehicle conditions, it is a great challenge to design gesture recognition systems due to variable driving conditions, complex backgrounds, and diversified gestures. In this paper, we propose a gesture recognition system based on frequency-modulated continuous-wave (FMCW) radar and transformer for an in-vehicle environment. Firstly, the original range-Doppler maps (RDMs), range-azimuth maps (RAMs), and range-elevation maps (REMs) of the time sequence of each gesture are obtained by radar signal processing. Then we preprocess the obtained data frames by region of interest (ROI) extraction, vibration removal algorithm, background removal algorithm, and standardization. We propose a transformer-based radar gesture recognition network named RGTNet. It fully extracts and fuses the spatial-temporal information of radar feature maps to complete the classification of various gestures. The experimental results show that our method can better complete the eight gesture classification tasks in the in-vehicle environment. The recognition accuracy is 97.56%.

Multi-Sensor Stockline Tracking within a Blast Furnace

2014 ◽  
Vol 701-702 ◽  
pp. 522-527
Author(s):  
Ji Dong Wei ◽  
Ge Guo
Keyword(s):  
Blast Furnace ◽  
Measurement Accuracy ◽  
Continuous Wave ◽  
Continuous Measurement ◽  
Contextual Information ◽  
Surface Profile ◽  
Radar Signal ◽  
Fmcw Radar ◽  
Synergistic Approach ◽  
Rms Error

The paper presents a synergistic approach for height tracking within a blast furnace (BF). The Frequency Modulated Continuous Wave (FMCW) radar has been employed to measure the height and surface profile of the burden surface. However the radar signal is easily disturbed, by the radar anomalies, during the process of continuous measurement. The data from rotating chute and charging switch provide information on contextual relevance with radar anomalies. An anomaly detection models has been developed to increase the measurement accuracy by utilizing contextual information. The approach has been validated on real BF. The root mean squared (RMS) error in the measured height is reduced by 17% when using the proposed approach compared to the case without it. The results suggest that the proposed approach successfully adapts to changes in the pattern and characteristics of the burden surface.

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