scholarly journals A Low-Complexity FMCW Surveillance Radar Algorithm Using Two Random Beat Signals

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 608 ◽  
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Sangdong Kim ◽  
Jonghun Lee
Keyword(s):  
Fourier Transform ◽  
Continuous Wave ◽  
Low Complexity ◽  
Radar System ◽  
Moving Target ◽  
Moving Targets ◽  
One Dimensional ◽  
Fmcw Radar ◽  
Target Indicator ◽  
Simulation Results

This paper proposes a low-complexity frequency-modulated continuous wave (FMCW) surveillance radar algorithm using random dual chirps in order to overcome the blind-speed problem and reduce the computational complexity. In surveillance radar algorithm, the most widely used moving target indicator (MTI) algorithm is proposed to effectively remove clutter. However, the MTI algorithm has a so-called ‘blind-speed problem’ that cannot detect a target of a specific velocity. In this paper, we try to solve the blind-speed problem of MTI algorithm by randomly selecting two beat signals selected for MTI for each frame. To further reduce the redundant complexity, the proposed algorithm first performs one-dimensional fast Fourier transform (FFT) for range detection and performs multidimensional FFT only when it is determined that a target exists at each frame. The simulation results show that despite low complexity, the proposed algorithm detects moving targets well by avoiding the problem of blind speed. Furthermore, the effectiveness of the proposed algorithm was verified by performing an experiment using the FMCW radar system in a real environment.

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 MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4295 ◽  
Author(s):  
Bong-seok Kim ◽  
Youngseok Jin ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Continuous Wave ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Field Of View ◽  
Music Algorithm ◽  
Trade Offs

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30°, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment.

Target Range and Velocity Measurement to Reduce False Targets in FMCW Automotive Anti-Collision Radar

2012 ◽  
Vol 253-255 ◽  
pp. 1410-1417 ◽  
Author(s):  
Zhi Gang Li ◽  
Qiong Chan Gu
Keyword(s):  
Computer Simulation ◽  
Theoretical Analysis ◽  
Continuous Wave ◽  
Target Range ◽  
Multiple Targets ◽  
Fmcw Radar ◽  
Wave Radar ◽  
Frequency Modulate ◽  
Inherent Problem ◽  
Simulation Results

For frequency modulate continuous wave radar, it is necessary and difficult to search the pairs of beat frequencies in an up-chirp mode and a down-chirp mode t o measure range and velocity of multiple targets. However, the inherent problem of FMCW radar is multiple targets detection. False targets can appearance because of mistaking the combination of these beat frequencies. A novel waveform named double-slope symmetrical saw-tooth wave is proposed and its corresponding algorithm is also introduced to resolve the problem of multiple targets detection for automotive anti-collision radar. Computer simulation results and theoretical analysis prove that the method is effective and practical for multiple targets detection in intelligence transportation system.

APPROACH OF MULTIPLE MOVING TARGETS DETECTION FOR MICROWAVE SURVEILLANCE SENSORS

2007 ◽  
Vol 04 (01) ◽  
pp. 57-68 ◽  
Author(s):  
WENQIN WANG
Keyword(s):  
Information Acquisition ◽  
Fractional Fourier Transform ◽  
Target Velocity ◽  
Fourier Domain ◽  
Moving Target ◽  
Moving Targets ◽  
True Position ◽  
Simulation Results ◽  
Multiple Moving Targets ◽  
Magnitude Improvement

Multiple moving targets detection is one of the fundamental problems in information acquisition. In this paper, the use of a transformable period and symmetrical linear frequency modulated (TPS-LFM) waveform for microwave surveillance sensor multiple moving targets identification, is proposed. In order to accurately estimate target's true position and velocity, a relatively unknown yet powerful technique, the so-called fractional Fourier transform (FrFT), is applied to estimate the moving target parameters. By mapping a target's signal onto a fractional Fourier axis, the FrFT permits a constant-velocity target to be focused in the fractional Fourier domain thereby affording orders of magnitude improvement in signal-clutter-ratio. Moving target velocity and position parameters are derived and expressed in terms of an optimum fractional angle and a measured fractional Fourier position, allowing a target to be accurately located. Moreover, to resolve the problem whereby weak targets are covered by the sidelobes of strong ones, the CLEAN technique is also applied. Simulation results show that the method is effective in estimating target velocity and position parameters for microwave surveillance sensors.

scholarly journals Improved FMCW Radar System for Multi-Target Detection of Human Respiration Vital Sign

2019 ◽  
Vol 19 (2) ◽  
pp. 38
Author(s):  
Hana Pratiwi ◽  
Mujib R. Hidayat ◽  
A. A. Pramudita ◽  
Fiky Y. Suratman
Keyword(s):  
Target Detection ◽  
Continuous Wave ◽  
Beat Frequency ◽  
Radar System ◽  
Small Displacement ◽  
Phase Detection ◽  
Detection Capability ◽  
Fmcw Radar ◽  
Large Bandwidth ◽  
Human Respiration

Frequency Modulated Continuous Wave (FMCW) radar system has been developed and applied for various needs. Based on the conventional FMCW radar concept, a large bandwidth is needed to detect small displacements in the chest wall or abdomen related with respiratory activity. To overcome the need for large bandwidths in detecting vital respiratory signs, several improvements to the FMCW system are proposed in this paper. The phase-detection concept has been elaborated in improving the capability of FMCW to detect the small displacement. In developing multi-target detection capability, range detection capability through beat frequency output needs to be combined with the phase-detection method. Theoretical and simulation studies were performed to investigate the concept of combining range detection and phase detection for detecting respiration on multi-target. The results show that the proposed method is well-performed in detecting the multi-target respiration in high noise reflection.

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.

Sign in / Sign up

Export Citation Format

Share Document