An anti-collision automotive FMCW Radar using time-domain interference detection and suppression

Nozawa, Takeshi; Makino, Yuya; Takaya, N.; Umehira, Masahiro; Takeda, Shigeki; Wang, Xiaoyan; Kuroda, Hiroshi

doi:10.1049/cp.2017.0366

Cited by 26 publications

(12 citation statements)

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“…However, these approaches would suppress targets' signals scattered from the same DOAs of the interferences. In [14], the interference is detected based on a threshold and then suppressed by windowing in time. In [15], an iterative modified method based on empirical mode decomposition is proposed to decompose the low-pass filter output of an FMCW radar as a series of empirical modes in the time domain while in [16] the wavelet denoising method is used to separate interferences from the useful signals.…”

Section: Introductionmentioning

confidence: 99%

CFAR-Based Interference Mitigation for FMCW Automotive Radar Systems

Wang

2022

IEEE Trans. Intell. Transport. Syst.

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In this paper, constant false alarm rate (CFAR) detector-based approaches are proposed for interference mitigation of Frequency modulated continuous wave (FMCW) radars. The proposed methods exploit the fact that after dechirping and low-pass filtering operations the targets' beat signals of FMCW radars are composed of exponential sinusoidal components while interferences exhibit short chirp waves within a sweep. The spectra of interferences in the time-frequency (tf ) domain are detected by employing a 1-D CFAR detector along each frequency bin and then the detected map is dilated as a mask for interference suppression. The proposed approaches are applicable to the scenarios in the presence of multiple interferences. Compared to the existing methods, the proposed methods reduce the power loss of useful signals and are very computationally efficient. Their interference mitigation performances are demonstrated through both numerical simulations and experimental results.

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Section: Introductionmentioning

confidence: 99%

CFAR-Based Interference Mitigation for FMCW Automotive Radar Systems

Wang

2022

IEEE Trans. Intell. Transport. Syst.

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“…Interference of any kind downgrades the detection capability and functionality of the radar system that is being interfered with, known as the 'victim radar' [3][4][5][6]. Consequently, various studies have been conducted on mitigating interference, using approaches with different processing costs and hardware complexity [7][8][9][10]. However, the structure of the interference varies according to the radar waveform type.…”

Section: Introductionmentioning

confidence: 99%

Automotive radar interference study for different radar waveform types

Kumbul

Uysal

Vaucher

et al. 2021

IET Radar Sonar & Navi

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Mutual interference between different radar waveforms used in automotive radar applications is studied. The existing interference analysis is extended to a generalised radar‐to‐radar interference equation that covers most of the common interference scenarios for automotive radar systems. The outcome of the generalised equation is demonstrated for a number of typical scenarios where radars with different continuously transmitting waveforms are involved. The proposed equation can be used to characterise the received interference and its features by analysing the instantaneous beat frequency of the victim radar. Moreover, an interference analysis of phase‐coded frequency‐modulated continuous waveforms is performed and demonstrated experimentally by using real‐time automotive radars for the first time in the literature. The experimental results corroborate the interference analysis of different waveforms and validate the proposed generalised interference equation under various conditions.

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“…Since the energies of the transmitted signals from interference radars are much higher than those of the echoed signals from targets, the beat frequency of the interference varies significantly. The interference signal can be treated as an impulse‐like signal in the time domain and as a white noise signal in the frequency domain [12]. A variety of threshold denoising algorithms have been proposed for white noise interference [13–16].…”

Section: Introductionmentioning

confidence: 99%