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 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 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 Super-Resolution-Based DOA Estimation with Wide Array Distance and Extrapolation for Vital FMCW Radar

2021 ◽  
Vol 21 (1) ◽  
pp. 23-34
Author(s):  
Sangdong Kim ◽  
Bongseok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee
Keyword(s):  
Continuous Wave ◽  
Super Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Low Complexity ◽  
Field Of View ◽  
Mean Square ◽  
Fmcw Radar ◽  
Simulation Results ◽  
Resolution Algorithm

This paper proposes a super-resolution-based direction-of-arrivals (DOA) estimation with wide array distance and extrapolation for vital frequency-modulated continuous-wave (FMCW) radar. Most super-resolution algorithms employ the distance between adjacent arrays of half a wavelength, i.e., λ/2. Meanwhile, in the case of narrow field of view of FMCW radar, the resolution of the angle is maintained by increasing the spacing between the arrays even if the number of arrays decreases. In order to employ these characteristics of array spacing and resolution, the proposed algorithm confirms whether or not to use the case where the distance between the adjacent arrays is greater than λ/2. In the case of an array distance >λ/2, a super-resolution algorithm is performed to obtain the enhanced DOA resolution. Moreover, the proposed algorithm virtually generates data between antennae by using extrapolation in order to further improve the performance of the resolution. The simulation results show that the proposed algorithm achieves the results of root-mean-square error similar to conventional super-resolution algorithms while maintaining low complexity. In order to further verify the performance of the proposed estimation algorithm, we demonstrate its employment in practice: experiments in a chamber room and an indoor room were conducted.

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 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.

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.

scholarly journals High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4018
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
High Efficiency ◽  
Continuous Wave ◽  
Super Resolution ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Fmcw Radar ◽  
Similar Performance ◽  
Average Complexity ◽  
Resolution Algorithm ◽  
And Performance

This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of 88% compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.

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