Limitations and capabilities of the slanted spectrogram analysis tool for SAR-based detection of multiple vibrating targets

Adebello, Jelili; Santhanam, Balu; Hayat, Majeed M.

doi:10.1109/acssc.2014.7094421

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…The time-frequency (TF) analysis method is an important tool to analyze the micro-Doppler effect. DFRFT is an effective method to estimate the time-varying accelerations, frequencies, and displacements associated with vibrating objects [10][11][12]. Moreover, a time-frequency tracking algorithm based on the high-order ambiguity function (HAF) is employed to reconstruct the instantaneous frequency law of the micro-Doppler [16,17].…”

Section: Comparison With Tf Analysis Method Dfrft-based Method and mentioning

confidence: 99%

“…In [8] and [9], the Doppler frequency of the rotating and vibrating targets was analyzed with smoothed pseudo Wigner-Ville distribution. A novel vibration estimation method based on the discrete fractional Fourier transform (DFRFT) was presented in [10][11][12]. The method in [13] with sinusoidal frequency modulation Fourier transform (SFMFT) was proposed to obtain the frequency spectrum of vibration traces.…”

Section: Introductionmentioning

confidence: 99%

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Target vibration estimation in SAR based on phase-analysis method

Xia

Huang

2016

EURASIP J. Adv. Signal Process.

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An efficient vibration estimation method for synthetic aperture radar (SAR) systems based on phase-analysis method is presented. Small vibrations, which consist of multiple frequency components and are usually rather weak, introduce phase modulation in radar echoes. They contain important signatures of objects. Extracting and analyzing the phase from radar echoes is one of the significant approaches to acquire vibration characteristics. In order to separate different targets in different range cells, the proposed method acts the range compression and range migration correction on the radar echoes, followed by extracting the phase history of each target's radar echoes. Since the phase history contains the time-varying ranges from the targets to airborne radar besides the vibration signal, we apply wavelet transform to the phase history to extract the vibration signal. Then the vibration signatures would be estimated quantitatively. The method is a more efficient and convenient approach to estimate the vibration amplitudes and frequencies of one or more targets, whose vibration signal is a single-frequency or multi-frequency signal. Moreover, it can be applied in the case where the airborne radar moves along the desirable or undesirable trajectory. Simulation results indicate that this method provides a larger range of estimable vibration frequency, higher estimation precision, and lower computation complexity.

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Section: Comparison With Tf Analysis Method Dfrft-based Method and mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Target vibration estimation in SAR based on phase-analysis method

Xia

Huang

2016

EURASIP J. Adv. Signal Process.

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“…However, in the presence of significant clutter, i.e., strong reflections by static targets located near the vibrating object, estimating the peak coordinates accurately becomes difficult. This difficulty is due to the manifestation of significant side lobes in the DFRFT spectrum [31].…”

Section: Rank-reduction and Subspace Methodsmentioning

confidence: 99%

SAR-based vibrometry using the fractional Fourier transform

et al. 2015

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A fundamental assumption when applying Synthetic Aperture Radar (SAR) to a ground scene is that all targets are motionless. If a target is not stationary, but instead vibrating in the scene, it will introduce a non-stationary phase modulation, termed the micro-Doppler effect, into the returned SAR signals. Previously, the authors proposed a pseudosubspace method, a modification to the Discrete Fractional Fourier Transform (DFRFT), which demonstrated success for estimating the instantaneous accelerations of vibrating objects. However, this method may not yield reliable results when clutter in the SAR image is strong. Simulations and experimental results have shown that the DFRFT method can yield reliable results when the signal-to-clutter ratio (SCR) > 8 dB. Here, we provide the capability to determine a target's frequency and amplitude in a low SCR environment by presenting two methods that can perform vibration estimations when SCR < 3 dB. The first method is a variation and continuation of the subspace approach proposed previously in conjunction with the DFRFT. In the second method, we employ the dual-beam SAR collection architecture combined with the extended Kalman filter (EKF) to extract information from the returned SAR signals about the vibrating target. We also show the potential for extending this SAR-based capability to remotely detect and classify objects housed inside buildings or other cover based on knowing the location of vibrations as well as the vibration histories of the vibrating structures that house the vibrating objects.

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“…In recent years, the DFRFT [7], [8], [9], [6] has become a useful time-frequency tool for multiple chirp parameter estimatiolin [5] and in particular it has been successfully applied to the problem of vibration estimation using SAR [2], [3], [4]. Direct DFRFT based estimation of the vibration frequency involves application of the DFRFT to the target return signal, peak coordinate location and translation of the peak coordinates to center-frequency and chirp-rate estimates using the peak-to-parameter mapping.…”

Section: Introductionmentioning

confidence: 99%

Clutter suppression in synthetic aperture radar targets using the DFRFT and subspace methods with rank reduction

Adebello

Santhanam

2015

2015 49th Asilomar Conference on Signals, Systems and Computers

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SAR based vibration estimation using discrete Fractional Fourier transform (DFRFT) analysis methods has gained attention in recent work on vibrometry. In the presence of significant clutter however, this estimation becomes challenging due to the presence of clutter induced peaks in the vibration spectra. In this paper, we incorporate rank reduction and filtering into a subspace DFRFT approach that results in significant peak enhancement along with an accompanying reduction in the associated mean square estimation errors when applied to simulated SAR and synthetic chirp data. The approach is further applied to vibration data gathered from a real GA-Lynx system and shown to produce a corresponding peak enhancement and clutter suppression in the vibration spectrum.

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Limitations and capabilities of the slanted spectrogram analysis tool for SAR-based detection of multiple vibrating targets

Cited by 4 publications

References 9 publications

Target vibration estimation in SAR based on phase-analysis method

Target vibration estimation in SAR based on phase-analysis method

SAR-based vibrometry using the fractional Fourier transform

Clutter suppression in synthetic aperture radar targets using the DFRFT and subspace methods with rank reduction

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