Research on Millimeter-Wave Radar Based Automotive Lateral Anti-Collision Warning System

2013 ◽  
Vol 278-280 ◽  
pp. 804-808 ◽  
Author(s):  
Xing Tian ◽  
Xin Bi ◽  
Yi Yang Liu ◽  
Jin Song Du
Keyword(s):  
Millimeter Wave ◽  
Frequency Modulation ◽  
Continuous Wave ◽  
Warning System ◽  
Difficult Problem ◽  
False Alarms ◽  
Collision Warning ◽  
Millimeter Wave Radar ◽  
Wave Radar ◽  
Frequency Modulation Continuous Wave

According to the reasons and features of car accidents happening in vehicles’ side areas, this paper designed and developed a kind of automotive lateral anti-collision warning system by frequency modulation continuous wave, based on the research on 24GHz linear frequency modulation continuous wave radar-probing system. The system designed in this paper will forecast the potential danger to drivers and avoid the accidents. The hardware structures, algorithm, program flows and working patterns of the warning system were introduced. Furthermore, pointing to the problem of false alarms, a kind of filtering method was presented creatively. This method improved the reliability of the warning system and the accuracy of the forecast. It filtered the disturbance coming from the side of the vehicles, and solved the difficult problem that prevented the millimeter-wave radar from being applied in automotive lateral anti-collision warning system. Finally, the experiment was designed and carried out. The result verified the rationality of the solution and the practicality of the system’s function.

scholarly journals Remote Monitoring of Human Vital Signs Based on 77-GHz mm-Wave FMCW Radar

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2999 ◽  
Author(s):  
Yong Wang ◽  
Wen Wang ◽  
Mu Zhou ◽  
Aihu Ren ◽  
Zengshan Tian
Keyword(s):  
Millimeter Wave ◽  
Human Body ◽  
Continuous Wave ◽  
Intermediate Frequency ◽  
Detection Methods ◽  
Discrete Wavelet ◽  
Phase Information ◽  
Millimeter Wave Radar ◽  
Wave Radar ◽  
Radar Sensing

In recent years, non-contact radar detection technology has been able to achieve long-term and long-range detection for the breathing and heartbeat signals. Compared with contact-based detection methods, it brings a more comfortable and a faster experience to the human body, and it has gradually received attention in the field of radar sensing. Therefore, this paper extends the application of millimeter-wave radar to the field of health care. The millimeter-wave radar first transmits the frequency-modulated continuous wave (FMCW) and collects the echo signals of the human body. Then, the phase information of the intermediate frequency (IF) signals including the breathing and heartbeat signals are extracted, and the Direct Current (DC) offset of the phase information is corrected using the circle center dynamic tracking algorithm. The extended differential and cross-multiply (DACM) is further applied for phase unwrapping. We propose two algorithms, namely the compressive sensing based on orthogonal matching pursuit (CS-OMP) algorithm and rigrsure adaptive soft threshold noise reduction based on discrete wavelet transform (RA-DWT) algorithm, to separate and reconstruct the breathing and heartbeat signals. Then, a frequency-domain fast Fourier transform and a time-domain autocorrelation estimation algorithm are proposed to calculate the respiratory and heartbeat rates. The proposed algorithms are compared with the contact-based detection ones. The results demonstrate that the proposed algorithms effectively suppress the noise and harmonic interference, and the accuracies of the proposed algorithms for both respiratory rate and heartbeat rate reach about 93%.

Study on Signal De-Noising for Vehicle Active Anti-Collision Warning Radar

2013 ◽  
Vol 401-403 ◽  
pp. 1368-1372
Author(s):  
Jian Hua Wang ◽  
Yun Cheng Wang ◽  
Fei Xie ◽  
Hai Feng Ding
Keyword(s):  
Simulation Analysis ◽  
Warning System ◽  
Intermediate Frequency ◽  
Signal Acquisition ◽  
Collision Warning ◽  
Millimeter Wave Radar ◽  
The Road ◽  
Wave Radar ◽  
Kalman Filter Algorithm ◽  
Signal Acquisition And Processing

The Vehicle Active Anti-collision Warning system often adopts the millimeter-wave radar with linear frequency-modulated continuous (FMCW) system as its signal acquisition and processing device. Affected by the road environment and their own devices, intermediate frequency (IF) signal inevitably exist in a variety of interference and noise. This paper proposed an iterative Kalman filter algorithm to remove the noise from IF signal. And used of MATLAB to do the simulation analysis. The analysis results show that the improved algorithm enhances the precision of de-noising effectively and meet the requirements of real-time and accuracy.

Photonic-Assisted Leakage Cancellation for Wideband Frequency Modulation Continuous-Wave Radar Transceiver

2020 ◽  
Vol 38 (6) ◽  
pp. 1178-1183 ◽  
Author(s):  
Peng Li ◽  
Lianshan Yan ◽  
Jia Ye ◽  
Xia Feng ◽  
Xihua Zou ◽  
...  
Keyword(s):  
Frequency Modulation ◽  
Continuous Wave ◽  
Wave Radar ◽  
Leakage Cancellation ◽  
Frequency Modulation Continuous Wave

scholarly journals Time-Frequency Spectral Signature of Limb Movements and Height Estimation Using Micro-Doppler Millimeter-Wave Radar

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4660
Author(s):  
Yael Balal ◽  
Nezah Balal ◽  
Yair Richter ◽  
Yosef Pinhasi
Keyword(s):  
Millimeter Wave ◽  
Continuous Wave ◽  
Animal Movement ◽  
Doppler Frequency ◽  
Spectral Signature ◽  
Millimeter Wave Radar ◽  
Time Frequency ◽  
Structure And Motion ◽  
W Band ◽  
Wave Radar

We present a technique for the identification of human and animal movement and height using a low power millimeter-wave radar. The detection was based on the transmission of a continuous wave and heterodyning the received signal reflected from the target to obtain micro-Doppler shifts associated with the target structure and motion. The algorithm enabled the extraction of target signatures from typical gestures and differentiated between humans, animals, and other ‘still’ objects. Analytical expressions were derived using a pendulum model to characterize the micro-Doppler frequency shifts due to the periodic motion of the human and animal limbs. The algorithm was demonstrated using millimeter-wave radar operating in the W-band. We employed a time–frequency distribution to analyze the detected signal and classify the type of targets.

scholarly journals FOD Detection Method Based on Iterative Adaptive Approach for Millimeter-Wave Radar

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1241
Author(s):  
Yangliang Wan ◽  
Xingdong Liang ◽  
Xiangxi Bu ◽  
Yunlong Liu
Keyword(s):  
False Alarm ◽  
Millimeter Wave ◽  
Detection Method ◽  
Super Resolution ◽  
False Alarms ◽  
Target Information ◽  
Millimeter Wave Radar ◽  
Resolution Capability ◽  
Wave Radar ◽  
Iterative Adaptive Approach

Using millimeter-wave radar to scan and detect small foreign object debris (FOD) on an airport runway surface is a popular solution in civil aviation safety. Since it is impossible to completely eliminate the interference reflections arising from strongly scattering targets or non-homogeneous clutter after clutter cancellation processing, the consequent high false alarm probability has become a key problem to be solved. In this article, we propose a new FOD detection method for interference suppression and false alarm reduction based on an iterative adaptive approach (IAA) algorithm, which is a non-parametric, weighted least squares-based iterative adaptive processing approach that can provide super-resolution capability. Specifically, we first obtain coarse FOD target information by data preprocessing in a conventional detection method. Then, a refined data processing step is conducted based on the IAA algorithm in the azimuth direction. Finally, multiple pieces of information from the two steps above are used to comprehensively distinguish false alarms by fusion processing; thus, we can acquire accurate FOD target information. Real airport data measured by a 93 GHz radar are used to validate the proposed method. Experimental results of the test scene, which include golf balls with a diameter of 43 mm, were placed about 300 m away from radar, which show that the proposed method can effectively reduce the number of false alarms when compared with a traditional FOD detection method. Although metal balls with a diameter of 50 mm were placed about 660 m away from radar, they also can obtain up to 2.2 times azimuth super-resolution capability.

Helicopter Near-Field Obstacle Warning System Based on Low-Cost Millimeter-Wave Radar Technology

2013 ◽  
Vol 61 (1) ◽  
pp. 658-665 ◽  
Author(s):  
Volker Ziegler ◽  
Falk Schubert ◽  
Benedikt Schulte ◽  
Andre Giere ◽  
Richard Koerber ◽  
...  
Keyword(s):  
Millimeter Wave ◽  
Low Cost ◽  
Near Field ◽  
Warning System ◽  
Millimeter Wave Radar ◽  
Wave Radar

scholarly journals Non-Contact Monitoring of Human Vital Signs Using FMCW Millimeter Wave Radar in the 120 GHz Band

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2732
Author(s):  
Wenjie Lv ◽  
Wangdong He ◽  
Xipeng Lin ◽  
Jungang Miao
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
Monitoring System ◽  
Millimeter Wave ◽  
Continuous Wave ◽  
Detection Accuracy ◽  
Narrow Beam ◽  
Millimeter Wave Radar ◽  
Fast Independent Component Analysis ◽  
Wave Radar

A non-contact heartbeat/respiratory rate monitoring system was designed using narrow beam millimeter wave radar. Equipped with a special low sidelobe and small-sized antenna lens at the front end of the receiving and transmitting antennas in the 120 GHz band of frequency-modulated continuous-wave (FMCW) system, this sensor system realizes the narrow beam control of radar, reduces the interference caused by the reflection of other objects in the measurement background, improves the signal-to-clutter ratio (SCR) of the intermediate frequency signal (IF), and reduces the complexity of the subsequent signal processing. In order to solve the problem that the accuracy of heart rate is easy to be interfered with by respiratory harmonics, an adaptive notch filter was applied to filter respiratory harmonics. Meanwhile, the heart rate obtained by fast Fourier transform (FFT) was modified by using the ratio of adjacent elements, which helped to improve the accuracy of heart rate detection. The experimental results show that when the monitoring system is 1 m away from the human body, the probability of respiratory rate detection error within ±2 times for eight volunteers can reach 90.48%, and the detection accuracy of the heart rate can reach 90.54%. Finally, short-term heart rate measurement was realized by means of improved empirical mode decomposition and fast independent component analysis algorithm.

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