Application of Fractional Fourier Transform to Moving Target Indication via Along-Track Interferometry

Chiu, Shen

doi:10.1155/asp.2005.3293

Cited by 27 publications

(16 citation statements)

References 12 publications

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“…In the real application, N a PRI 2 is used as the factor of coordinate transformation in digitalized computation [26,27]. Back to (29), the STFRFT of an individual scattering center is decided by STF K a (η, u).…”

Section: Trajectories Separation Based On Stfrftmentioning

confidence: 99%

Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm

Song

Gao

Zhu

et al. 2016

EURASIP J. Adv. Signal Process.

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This paper introduces a modified random sample consensus (M-RANSAC) and short-time fractional Fourier transform (STFRFT)-based algorithm for feature extraction of synthetic aperture radar (SAR) scattering centers. In this algorithm, the range migration curve (RMC) of a scattering center is formulated as a parametric model. By estimating these parameters, the backscattering envelope of scattering center, corresponding to the backscattering variation in synthetic aperture time, is extracted directly from a time-domain range-compressed signal. The estimated parameters can also reconstruct the geographical location and along-track velocity of scattering centers. Thus, even without knowing explicit knowledge of platform velocity and forming a SAR image, this algorithm is capable of realizing feature extraction. To estimate parameters scatter by scatter, M-RANSAC approach is proposed as an implementary method with iterative procedure. In the iterations, fitting precision indicator (FPI) works cooperatively with construction fitness coefficient (CFC) to determine the optimal parameters of different scattering centers. Adapting this method to more general cases, STFRFT is introduced to separate the overlapped trajectories of RMCs of scattering centers. The root mean squared errors (RMSEs) of parameter estimation are close to their Cramér-Rao lower bounds (CRLB). The effectiveness of feature extraction based on the devised algorithm is validated by both simulated and real SAR data.

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Section: Trajectories Separation Based On Stfrftmentioning

confidence: 99%

Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm

Song

Gao

Zhu

et al. 2016

EURASIP J. Adv. Signal Process.

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“…Equation (8) can be expanded to (12), see equation at the bottom of the next page). It is noticed from (12) that, if v y = 0, there will be |S c1 (t, τ )| = 0; hence, at this step, the clutter has been successfully canceled by this method.…”

Section: Waveform Diversity-basedmentioning

confidence: 99%

“…In [12], the author developed a matched-filter-equivalent fractional Fourier transform (FrFT) algorithm to focus the ATI SAR GMTI data. In [13], several ATI SAR GMTI modes for RADARSAT-2 are described.…”

Section: Introductionmentioning

confidence: 99%

Two-Antenna SAR With Waveform Diversity for Ground Moving Target Indication

Wang

Shao

2014

IEEE Geosci. Remote Sensing Lett.

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Along-track interferometry (ATI) and displaced phase center antenna (DPCA) are two representative synthetic aperture radar (SAR) ground moving target indication (GMTI) techniques. However, the former is a clutter-limited detector, whereas the latter is a noise-limited detector. In this letter, we propose a two-antenna SAR with waveform diversity for GMTI. The two antennas placed in the azimuth dimension simultaneously transmit two orthogonal waveforms, namely, the up-and down-chirp waveforms. In doing so, four independent transmit-receive channels are obtained for the receiver, and thus, an efficient GMTI is developed by cooperatively utilizing the ATI GMTI and DPCA GMTI processing techniques. This method first uses the DPCA technique to cancel clutter and then the ATI technique to suppress noise. Next, the fractional Fourier transform is employed to estimate the Doppler parameters and corresponding reference filters are designed to focus the moving targets. The proposed approach cooperatively utilizes the advantages of ATI and DPCA GMTI techniques and overcomes their disadvantages. It does not prerequire knowledge of the target's across-track velocity. The effectiveness is verified by simulation results.Index Terms-Along-track interferometry (ATI), displaced phase center antenna (DPCA), ground moving target indication (GMTI), Synthetic aperture radar (SAR), waveform diversity.

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“…For SAR Ground Moving Target Indication (SAR-GMTI), the underlying assumption that the radar scene is stationary must be extended to include nonstationary scenes or moving targets. This can be quite easily accomplished for the case of an airborne platform [38], which is assumed to be moving along a straight line and transmitting uniformly spaced pulses. This assumption requires good platform motion compensation and good control of the PRF as a function of ground speed.…”

Section: Equations Of Motion Of a Moving Targetmentioning

confidence: 99%

Moving Target Indication via RADARSAT-2 Multichannel Synthetic Aperture Radar Processing

Chiu

Dragosevic²

2009

EURASIP J. Adv. Signal Process.

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With the recent launches of the German TerraSAR-X and the Canadian RADARSAT-2, both equipped with phased array antennas and multiple receiver channels, synthetic aperture radar, ground moving target indication (SAR-GMTI) data are now routinely being acquired from space. Defence R&D Canada has been conducting SAR-GMTI trials to assess the performance and limitations of the RADARSAT-2 GMTI system. Several SAR-GMTI modes developed for RADARSAT-2 are described and preliminary test results of these modes are presented. Detailed equations of motion of a moving target for multiaperture spaceborne SAR geometry are derived and a moving target parameter estimation algorithm developed for RADARSAT-2 (called the Fractrum Estimator) is presented. Limitations of the simple dual-aperture SAR-GMTI mode are analysed as a function of the signal-to-noise ratio and target speed. Recently acquired RADARSAT-2 GMTI data are used to demonstrate the capability of different system modes and to validate the signal model and the algorithm.

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Application of Fractional Fourier Transform to Moving Target Indication via Along-Track Interferometry

Cited by 27 publications

References 12 publications

Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm

Feature extraction of SAR scattering centers using M-RANSAC and STFRFT-based algorithm

Two-Antenna SAR With Waveform Diversity for Ground Moving Target Indication

Moving Target Indication via RADARSAT-2 Multichannel Synthetic Aperture Radar Processing

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