Design and Implementation of FMCW Surveillance Radar Based on Dual Chirps

Lee

et al. 2020

Self Cite

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.

Section: Introductionmentioning

confidence: 99%

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

Lee

et al. 2020

Self Cite

“…As one of the most promising among the various radar techniques, frequency-modulated continuous wave (FMCW) radar systems have been studied [6,7,8,9]. In FMCW radar systems, by multiplying the received signal by the transmitted signal, linear combination of sinusoid signals with low frequencies, so-called ‘beat signal’ can be directly obtained.…”

Section: Introductionmentioning

confidence: 99%

“…To distinguish between stationary target and moving target, the moving target indicator (MTI) algorithms have been employed and discussed [4] and their applications include the surveillance, indoor tracking and vehicle radar systems [9]. More recently, in [8,9], MTI algorithms for FMCW radar systems have been proposed. In [8], this algorithm effectively detects the moving targets by performing FFT on only difference between two beat signals.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

“…Meanwhile, there have been several studies on frequency-modulated continuous wave (FMCW) radar systems as they have many advantages, such as low cost and low complexity [7][8][9][10][11][12][13]. Compared to pulsed radar, which requires large bandwidth and high cost, FMCW radar systems have relatively narrow bandwidth and low transmitted peak power, thus FMCW radar can meet certain range and velocity requirements with relatively low cost hardware and architectures [7][8][9][10][11][12][13]. In FMCW radar systems, a fast Fourier transform (FFT) is typically used as an estimator for parameters such as range, velocity, and angle.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], meanwhile, a low-complexity algorithm has been proposed by employing difference only two beat signals in order to effectively detect moving target. In the cases of stationary target and…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.clutter, there is no Doppler effect. Hence, two beat signals are the same except for noise term and thus the difference of two beat signals contains only noise term. On the other hand, in the case of moving target, there is Doppler effect due to the moving target and thus the difference of them contains the range information of moving target. However, this algorithm might miss the moving target with certain velocity because this algorithm fixedly employs two beat signals. In order to overcome this disadvantage, an FMCW radar algorithm has been proposed by randomly employing two beat signals in [14]. This algorithm effectively avoids missing a target with a certain velocity by randomly selecting two beat signals every frame. In addition, this algorithm performs an angle detection algorithm only if there is a moving target. Therefore, this algorithm reduces the overall complexity. However, this algorithm has still a disadvantage in that it does not detect the velocity of the target. This is because the difference between the two beat signals is used to reduce the complexity of the moving target detection process and in this process, information necessary for the velocity detection of the target is lost.Meanwhile, in [15][16][17][18], low-complexity detection algorithms for FMCW radar have been proposed which intend to reduce the number of FFTs compared to a full-dimension FFT-based FMCW radar algorithm. These algorithms determine a region of interest (ROI), thus reducing the number of inputs in the FFTs for Doppler estimation. However, there is still unnecessary computational complexity in these algorithms, although the complexity is reduced. The number of range bins used as the input in FFTs for Doppler estimation depends on the number of targets. In this algorithm, all chirp signals are used in an FFT to determine the range bins in which peaks exist. However, there is a disadvantage in that the number of range bins calculated in the first FFT for range estimation is too large compared to the number of range bins used as inputs in the FFT fo...