FMCW Signal Detection and Parameter Extraction by Cross Wigner–Hough Transform

Erdogan, A. Yasin; Gulum, Taylan O.; Durak–Ata, Lütfiye; Yıldırım, Tülay; Pace, P.E.

doi:10.1109/taes.2017.2650518

Cited by 30 publications

(17 citation statements)

References 23 publications

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“…A frequency modulated continuous wave (FMCW) is a representative technique that is used in short-range applications such as proximity fuses, level measurements, and collision avoidance scenarios [13][14][15][16][17]. Early CASs used long slow linear frequency modulation (LFM), which is similar to the long-range version of the FMCW.…”

Section: A Related Workmentioning

confidence: 99%

Distance Estimation of High-Speed Underwater Targets Based on a Frequency-Coded Continuous Wave

Park

Kim

2020

IEEE Access

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Section: A Related Workmentioning

confidence: 99%

Distance Estimation of High-Speed Underwater Targets Based on a Frequency-Coded Continuous Wave

Park

Kim

2020

IEEE Access

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“…In [1], Wigner-Ville distribution (WVD) is used as a time frequency (T-F) detection technique and it is combined with Hough-Radon transform (HT) to identify the parameters of radar frequency modulated continuous waveform (FMCW) at low signal to noise ratio (SNR) levels. In [2], WD and HT are used to detect and extract FMCW signals' parameters. A proposed algorithm of Cross-Wigner-Ville and HT (XWHT) is used for detection and parameter extraction of FMCW signals depending on the crossterms created by WD [2].…”

Section: Introductionmentioning

confidence: 99%

“…In [2], WD and HT are used to detect and extract FMCW signals' parameters. A proposed algorithm of Cross-Wigner-Ville and HT (XWHT) is used for detection and parameter extraction of FMCW signals depending on the crossterms created by WD [2]. The performance of the proposed method is compared with other Wigner-Hough transform-based methods in terms of transform speed, parameter extraction, and detection performance.…”

Section: Introductionmentioning

confidence: 99%

Overlapped Chirp Signals’ Parameters Estimation in Radar ESM Station

Elgamel

2022

AiMT

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Three consecutive algorithms are used to estimate the number of multiple overlapped pulsed received chirp signals and their parameters in the electronic support measures (ESM) station noisy receiving window at low signal to noise ratio. The first consecutive algorithm is used to estimate both the number of multiple overlapped received radar signals and the chirp rate of each one in the receiving window. Then, the second consecutive algorithm is used to minimize the additive noise and/or interference in the receiving window by filtering each received chirp signal in the corresponding fractional Fourier domain. The third consecutive algorithm based on WD and Hough transform is used to estimate both the received chirp signal duration and the received chirp signal bandwidth.

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“…We engage in the class of signals where the instantaneous frequency particularly or basically determines the time-frequency signatures of the signal source. A successful application of time-frequency distribution desires prior knowledge for the signal source in order that the most advisable distribution is preferred [10]. In this article, Wigner-Ville distribution (WVD) is considered as the timefrequency distribution representation since it provides the most energy concentration in time-frequency domains, displays the non-stationary properties of the signal, and satisfies the marginal conditions [11].…”

Section: Introductionmentioning

confidence: 99%

Spatial time-frequency distribution of cross term-based direction-of-arrival estimation for weak non-stationary signal

Shao

Liu

et al. 2019

J Wireless Com Network

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In the radar array signal processing direction of arrival (DOA), the estimation of weak non-stationary signal is an important and difficult problem when both strong and weak signals are coexisting particularly because the weak non-stationary signals are often submerged in noise. In this paper, we proposed a novelty method to estimate the direction of arrival (DOA) of weak non-stationary signal in scenario for strong non-stationary interference signals and Gaussian white noise. The method utilizes spatial time-frequency distribution (STFD) of cross terms rather than suppressing cross terms in time-frequency analysis. The STFD of cross terms are introduced as an alternative matrix, which is similar to data covariance matrix in multiple signal classification (MUSIC), for the DOA estimation of a weak non-stationary signal. The cross-term amplitude of the strong and weak signals is usually above the noise and is easier to use than the auto-term of the weak signal. In the cross term, the information of the weak signal is included, and the auto-term of these weak signals is difficult to extract directly. The ability to incorporate the STFD of cross terms empowers information about a weak non-stationary signal for DOA estimation, leading to improved signal estimates for direction finding. The method based on the STFD of cross terms for DOA estimation of the weak non-stationary signal is revealed to outperform the time-frequency MUSIC and traditional MUSIC algorithm by simulation, respectively. This method has the advantages of the time-frequency direction finding method and also deals with the situation of weak signals. When the strong and weak signals exist at the same time and the two angles are similar, the cross-terms can be used to perform DOA estimation on the weak signal.

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FMCW Signal Detection and Parameter Extraction by Cross Wigner–Hough Transform

Cited by 30 publications

References 23 publications

Distance Estimation of High-Speed Underwater Targets Based on a Frequency-Coded Continuous Wave

Distance Estimation of High-Speed Underwater Targets Based on a Frequency-Coded Continuous Wave

Overlapped Chirp Signals’ Parameters Estimation in Radar ESM Station

Spatial time-frequency distribution of cross term-based direction-of-arrival estimation for weak non-stationary signal

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