Parameter extraction of FMCW modulated radar signals using Wigner-Hough transform

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

doi:10.1109/cinti.2011.6108551

Cited by 21 publications

(16 citation statements)

References 6 publications

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“…[1]. In HT, the maximum intensity points may correspond to either an LFM component or a cross-term, in HRT however, maximum intensity points directly correspond to FMCW components.…”

Section: Methodsmentioning

confidence: 97%

“…The difficulty of detecting a signal and determining its major parameters, at -9 dB SNR, can be seen from Figure 3. HT, as defined in [1], was not successful enough under challenging T-F images like Figure 3. The proposed method makes the required improvement on detecting the signal components even at -9 dB SNR levels.…”

Section: Methodsmentioning

confidence: 98%

“…In [1], as a computationally more efficient tool, Wigner-Hough method, was used for FMCW signal parameter extraction. This latter method performed well down to SNR levels of -6 dB, however noise levels made it hard to distinguish between WVD cross-terms and FM components below -6 dB SNR.…”

Section: Wvd-hough-radon Transformmentioning

confidence: 99%

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A parameter extraction technique for FMCW radar signals using Wigner-Hough-Radon transform

Gulum

Erdogan

Yıldırım

et al. 2012

2012 IEEE Radar Conference

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An autonomous parameter extraction algorithm for frequency modulated continuous wave (FMCW) radar signals using Wigner-Ville Distribution (WVD)-Hough transform was investigated in [1] and extraction of polyphase radar modulation parameters using a Wigner-Ville distribution-Radon transform was investigated in [2]. The algorithm in [1] produced very dependable results with as low as -6 dB SNR levels, however some degradation has been observed below -6 dB SNR. The proposed approach in this study uses the WVD as a timefrequency (T-F) detection technique and combined HoughRadon transform (HRT) to identify the parameters of the modulation.We showed that our algorithm can extract FMCW radar modulation parameters at low SNR levels, such as -9 dB, efficiently.

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“…[1]. In HT, the maximum intensity points may correspond to either an LFM component or a cross-term, in HRT however, maximum intensity points directly correspond to FMCW components.…”

Section: Methodsmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 98%

See 1 more Smart Citation

A parameter extraction technique for FMCW radar signals using Wigner-Hough-Radon transform

Gulum

Erdogan

Yıldırım

et al. 2012

2012 IEEE Radar Conference

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“…The number of lines transferred to ( , ) r θ space is kept in ( , ) C r θ counter. Details of the method can be found in [10]. Given that…”

Section: Wigner-hough Transformmentioning

confidence: 99%

“…The combination of PWVD and Wigner-Hough Transform (WHT), maps the signal energy from the Wigner spectrum to a parameter space in which detection and parameter extraction of signals can be performed simultaneously and optimally [9,10].…”

Section: Introductionmentioning

confidence: 99%

PWVD resolution considerations for LFMCW signal detection by WHT

Gulum

Erdogan

Guner

et al. 2014

2014 20th International Conference on Microwaves, Radar and Wireless Communications (MIKON)

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Abstract-Linear Frequency Modulated ContinuousWaveform (LFMCW) is one of the most common waveforms used in low probability of intercept (LPI) radars. The WignerHough transform (WHT) is a powerful technique for detection and parameter extraction of LFMCW waveforms that can be employed by Electronic Support Receivers. For a fast detection and a timely response to the adversary emitter, the selection of the pseudo Wigner-Ville distribution (PWVD) window length is critical. In this work we analyze the relation between PWVD window length, WHT span angle and span resolution. It is shown that faster correct detections can be achieved by decreasing the PWVD window length and consequently decreasing the WHT plane. A rapid detection and apiori estimation of target emitter signal chirp rate will allow enough time for a fine tuned postprocessing which can be applied specifically to the a priori estimates.

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