scholarly journals Low-Complexity Joint Range and Doppler FMCW Radar Algorithm Based on Number of Targets

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 51 ◽  
Author(s):  
Bong-seok Kim ◽  
Sangdong Kim ◽  
Youngseok Jin ◽  
Jonghun Lee
Keyword(s):  
Continuous Wave ◽  
Region Of Interest ◽  
Doppler Frequency ◽  
Low Complexity ◽  
Process Unit ◽  
Central Process ◽  
Fmcw Radar ◽  
Radar Systems ◽  
Lower Complexity ◽  
Joint Range

A low-complexity joint range and Doppler frequency-modulated continuous wave (FMCW) radar algorithm based on the number of targets is proposed in this paper. This paper introduces two low-complexity FMCW radar algorithms, that is, region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based algorithms. We find the low-complexity condition of each algorithm by analyzing the complexity of these algorithms. From this analysis, it is found that the number of targets is an important factor in determining complexity. Based on this result, the proposed algorithm selects a low-complexity algorithm between two algorithms depending the estimated number of targets and thus achieves lower complexity compared two low-complexity algorithms introduced. The experimental results using real FMCW radar systems show that the proposed algorithm works well in a real environment. Moreover, central process unit time and count of float pointing are shown as a measure of complexity.

scholarly journals Low-Complexity 2D-MUSIC for Joint Range and Angle Estimation of Frequency Modulated Continuous-Wave Radar

2021 ◽  
Vol 21 (5) ◽  
pp. 399-405
Author(s):  
Yongchul Jung ◽  
Seunghyeok Lee ◽  
Seongjoo Lee ◽  
Yunho Jung
Keyword(s):  
Continuous Wave ◽  
Low Complexity ◽  
Processing Technique ◽  
Angle Estimation ◽  
Multiple Signal Classification ◽  
Fmcw Radar ◽  
Radar Systems ◽  
Wave Radar ◽  
Preprocessing Technique ◽  
Joint Range

A pre-processing technique is proposed to reduce the complexity of two-dimensional multiple signal classification (2D-MUSIC) for the joint range and angle estimation of frequency-modulated continuous-wave (FMCW) radar systems. By using the central symmetry of the angle steering vector from a uniform linear array (ULA) antenna and the linearity of the beat signal in the FMCW radar, this preprocessing technique transforms 2D-MUSIC from complex values into real values. To compare the computational complexity of the proposed algorithm with the conventional 2D-MUSIC, we measured the CPU processing time for various numbers of snapshots, and the evaluation results indicated that the 2D-MUSIC with the proposed pre-processing technique is approximately three times faster than the conventional 2D-MUSIC.

scholarly journals Low-Complexity-Based RD-MUSIC with Extrapolation for Joint TOA and DOA at Automotive FMCW Radar Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Sangdong Kim ◽  
Bongseok Kim ◽  
Jonghun Lee
Keyword(s):  
High Resolution ◽  
Continuous Wave ◽  
Low Complexity ◽  
Fmcw Radar ◽  
Multiple Parameters ◽  
Extrapolation Algorithm ◽  
Radar Systems ◽  
Multiple Vehicles ◽  
Resolution Algorithm ◽  
On The Road

Low-complexity-based reduced-dimension–multiple-signal classification (RD-MUSIC) is proposed with extrapolation for joint time delay of arrivals (TOA) and direction of arrivals (DOA) at automotive frequency-modulated continuous-wave (FMCW) radar systems. When a vehicle is driving on the road, the automotive FMCW radar can estimate the position of multiple other vehicles, because it can estimate multiple parameters, such as TOA and DOA. Over time, the requirement of the accuracy and resolution parameters of automotive FMCW radar is increasing. To accurately estimate the parameters of multiple vehicles, such as range and angle, it is difficult to use a low-resolution algorithm, such as the two-dimensional fast Fourier transform. To improve parameter estimation performance, high-resolution algorithms, such as the 2D-MUSIC, are required. However, the conventional high-resolution methods have a high complexity and, thus, are not applicable to a real-time radar system for a vehicle. Therefore, in this work, a low-complexity RD-MUSIC with extrapolation algorithm is proposed to have a resolution similar to that of a high-resolution algorithm to estimate the position of other vehicles. Compared with conventional low complexity high resolution, in experimental results, the proposed method had better performance.

scholarly journals Low-Complexity Super-Resolution Detection for Range-Vital Doppler Estimation FMCW Radar

2021 ◽  
Vol 21 (3) ◽  
pp. 236-245
Author(s):  
Bongseok Kim ◽  
Youngseok Jin ◽  
Youngdoo Choi ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
Continuous Wave ◽  
Low Cost ◽  
Phase Variation ◽  
Super Resolution ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Music Algorithm ◽  
Fmcw Radar ◽  
Detection Algorithms ◽  
Simulation And Experiment

This paper proposes low-complexity super-resolution detection for range-vital Doppler estimation frequency-modulated continuous wave (FMCW) radar. In regards to vital radar, and in order to estimate joint range and vital Doppler information such as the human heartbeat and respiration, two-dimensional (2D) detection algorithms such as 2D-FFT (fast Fourier transform) and 2D-MUSIC (multiple signal classification) are required. However, due to the high complexity of 2D full-search algorithms, it is difficult to apply this process to low-cost vital FMCW systems. In this paper, we propose a method to estimate the range and vital Doppler parameters by using 1D-FFT and 1D-MUSIC algorithms, respectively. Among 1D-FFT outputs for range detection, we extract 1D-FFT results based solely on human target information with phase variation of respiration for each chirp; subsequently, the 1D-MUSIC algorithm is employed to obtain accurate vital Doppler results. By reducing the dimensions of the estimation algorithm from 2D to 1D, the computational burden is reduced. In order to verify the performance of the proposed algorithm, we compare the Monte Carlo simulation and root-mean-square error results. The simulation and experiment results show that the complexity of the proposed algorithm is significantly lower than that of an algorithm detecting signals in several regions.

Gas Flow Monitoring in High and Low Reynolds Regimes Based on Compensated FMCW-Radar Phase Measurements

Frequenz ◽  
2017 ◽  
Vol 71 (3-4) ◽  
Author(s):  
Birk Hattenhorst ◽  
Christoph Baer ◽  
Thomas Musch ◽  
Timo Jaeschke ◽  
Nils Pohl
Keyword(s):  
Gas Flow ◽  
Continuous Wave ◽  
Phase Measurements ◽  
Fmcw Radar ◽  
Flow Monitoring ◽  
Radar Systems ◽  
Wave Radar ◽  
Measurement Signal ◽  
Gaseous Media ◽  
Low Jitter

AbstractIn this contribution, a composite measurement concept for the gas flow determination in diverse stream scenarios is presented. The approach utilizes the pressure- and mixing-dependent relative permittivity of gaseous media, which, in case of a vortex or a marker gas, creates a detectable variation in the measuring beam of the radar. Since the measurement effect is very small, phase measurements based on highly precise and low jitter frequency-modulated continuous-wave radar systems in different frequency bands are applied. Moreover, disturbances caused by vibrations of the measurement setup are compensated out of the measurement signal.

scholarly journals Long-Range Drone Detection of 24 G FMCW Radar with E-plane Sectoral Horn Array

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4171 ◽  
Author(s):  
Byunggil Choi ◽  
Daegun Oh ◽  
Sunwoo Kim ◽  
Jong-Wha Chong ◽  
Ying-Chun Li
Keyword(s):  
Long Range ◽  
Continuous Wave ◽  
Radar System ◽  
Lens Antenna ◽  
Horn Antennas ◽  
Fmcw Radar ◽  
Outdoor Environments ◽  
Joint Range ◽  
Sectoral Horn ◽  
24 Ghz

In this work, a 24-GHz frequency-modulated continuous-wave (FMCW) radar system with two sectoral horn antennas and one transmitting lens antenna for long-range drone detection is presented. The present work demonstrates the detection of a quadcopter-type drone using the implemented radar system up to a distance of 1 km. Moreover, a 3D subspace-based algorithm is proposed for the joint range-azimuth-Doppler estimation of long-range drone detection. The effectiveness of the long-range drone detection is verified with the implemented radar system through a variety of experiments in outdoor environments. This is the first such demonstration for long-range drone detection with a 24-GHz FMCW radar.

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-sensor Doppler radar for machine tool collision detection

2014 ◽  
Vol 12 ◽  
pp. 35-41 ◽  
Author(s):  
T. J. Wächter ◽  
U. Siart ◽  
T. F. Eibert ◽  
S. Bonerz
Keyword(s):  
Moving Objects ◽  
Continuous Wave ◽  
Doppler Radar ◽  
Frequency Estimation ◽  
Control Unit ◽  
Doppler Frequency ◽  
Low Complexity ◽  
Abstract Machine ◽  
Human Errors ◽  
Spatially Distributed

Abstract. Machine damage due to tool collisions is a widespread issue in milling production. These collisions are typically caused by human errors. A solution for this problem is proposed based on a low-complexity 24 GHz continuous wave (CW) radar system. The developed monitoring system is able to detect moving objects by evaluating the Doppler shift. It combines incoherent information from several spatially distributed Doppler sensors and estimates the distance between an object and the sensors. The specially designed compact prototype contains up to five radar sensor modules and amplifiers yet fits into the limited available space. In this first approach we concentrate on the Doppler-based positioning of a single moving target. The recorded signals are preprocessed in order to remove noise and interference from the machinery hall. We conducted and processed system measurements with this prototype. The Doppler frequency estimation and the object position obtained after signal conditioning and processing with the developed algorithm were in good agreement with the reference coordinates provided by the machine's control unit.

Simulation of a Frequency-Modulated Continuous-Wave (FMCW) Radar Using Fast Fourier Transforms (FFT)

2019 ◽  
pp. 196-211
Author(s):  
Akbar Eslami
Keyword(s):  
Continuous Wave ◽  
Fourier Transforms ◽  
Three Dimensional ◽  
Fast Fourier Transforms ◽  
Target Velocity ◽  
Signal Power ◽  
Moving Targets ◽  
Fmcw Radar ◽  
Radar Systems ◽  
Dimensional Graph

Frequency-modulated continuous-wave (FMCW) radar systems send known frequency signals to moving targets and receive the signal back to detectors. FMCW systems can be used to measure exact heights of landing aircrafts. In addition, they are used in early warning radar systems and in proximity sensors. The advantage of using these radar signals is that the object target velocity and range can be quickly calculated using fast Fourier transforms (FFT). Taking the row-wise FFT of the signal matrix gives range information in form of range bins. Then taking column-wise FFT enables displaying the velocity for each range bin. The three-dimensional graph of the resulting matrix gives a signal power plot with respect to both the range bin numbers and their velocity.

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