Joint time-frequency transform for radar range-Doppler imaging

Chen, V.C.; Qian, Shie

doi:10.1109/7.670330

Cited by 355 publications

(161 citation statements)

References 7 publications

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“…Thus, each time-domain signal along the 256 bursts is rearranged into a (128×64) time-frequency grid. Note that the number of time samples, which is also the number of temporal frames, is not necessary to be the same as the number of bursts because there is little Doppler variation between sufficiently dense time samples [15,16]. In Figure 7, the ISAR images of the point-scatterer set 1 are depicted by applying the STFT and the DGR.…”

Section: Application To Radar Signals From Ideal Point-scatterer Setsmentioning

confidence: 99%

“…The time-varying rotation angle θ(t) is assumed to be Ωt where Ω is the angular speed. The rotation-induced Doppler shift derived from Equation (1) is characterized by the time-varying term Ω 2 t [15,16]. Thus, for a relatively long coherent processing time (CPT) and a fast angular speed, the FT is replaced by the TFT in ISAR imaging.…”

Section: The Radar Signal Model and The Principle Of Tft-based Isar Imentioning

confidence: 99%

“…Since Chen et al first introduced the concept of TFT-based radar imaging [15,16], various time-frequency transforms have been developed for ISAR applications. Linear TFTs, such as the shorttime Fourier transform (STFT) and the wavelet transform (WT) are well-known methods and are conceptually simple to implement [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Despite their operational simplicity, the resolution limitation always arises from the window-induced Heisenberg-Gabor limit. For more enhanced focusing performance, bilinear TFTs [16,19,20] and adaptive TFTs with optimization methods [21][22][23] were subsequently proposed. Although they significantly improved the image smearing problem, these methods were still restrictive in real-time signal processing because of their computational burden.…”

Section: Introductionmentioning

confidence: 99%

“…For better performance of ISAR imaging in radar target recognition, the smeared ISAR image needs to be focused by compensating for the target motion, which is also called as the ISAR motion compensation [10][11][12][13][14]. Recently, time-frequency transforms (TFTs) have been widely employed in order to effectively reflect the time-dependent characteristic of the Doppler frequency [15][16][17][18][19][20][21][22][23]. In general, there are two requirements in TFT-based ISAR image focusing.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Enhanced and Efficient Isar Image Focusing Using the Discrete Gabor Representation in an Oversampling Scheme

Park¹,

Myung²

2013

PIER

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Abstract-Inverse synthetic aperture radar (ISAR) imaging is one of the most well-known techniques of radar target recognition. One of the most important issues in ISAR imaging is the improvement of the image smeared by a moving target. In this paper, we propose the discrete Gabor representation (DGR) in an oversampling scheme as an effective means of obtaining a well-focused ISAR image with a short calculation time. In contrast to other linear time-frequency transforms (TFTs), the DGR obtains Gabor coefficients using the analysis window frames derived from the clearly defined Gaussian-type synthesis window. The oversampling scheme of the DGR leads to accurate calculations of the Gabor coefficients, which denote signal timefrequency amplitude. Since each Gabor coefficient is compartmentally assigned to the associated unit cell of the time-frequency grid, the DGR can show an excellent time-frequency concentration and can effectively discriminate the Doppler components of prominent pointscatterers. The application results demonstrate that the DGR not only has enhanced focusing performance but also retains computational efficiency. The DGR in the oversampling scheme is expected to facilitate high-quality ISAR imaging in radar target recognition.

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Section: Application To Radar Signals From Ideal Point-scatterer Setsmentioning

confidence: 99%

Section: The Radar Signal Model and The Principle Of Tft-based Isar Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Enhanced and Efficient Isar Image Focusing Using the Discrete Gabor Representation in an Oversampling Scheme

Park¹,

Myung²

2013

PIER

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Radar Imaging

Chen

2005

Encyclopedia of RF and Microwave Engineering

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Radar imaging is an imaging method obtained by processing radar signals reflected from an object and generating an image of that object. The purpose of this article is to introduce basic concepts of radar imaging, including radar imaging geometry, synthetic aperture, stripmap mode, spotlight mode, and inverse mode. This article summarizes algorithms for radar imaging, including the range–Doppler algorithm, range migration algorithm, chirp‐scale algorithm, polar formatting algorithm, phase gradient algorithm, prominent point processing algorithm, and time–frequency‐based image formation algorithm. Issues in radar imaging of moving targets are also introduced.

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Radar Imaging

Chen

2005

Encyclopedia of RF and Microwave Engineering

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Joint time-frequency transform for radar range-Doppler imaging

Cited by 355 publications

References 7 publications

Enhanced and Efficient Isar Image Focusing Using the Discrete Gabor Representation in an Oversampling Scheme

Enhanced and Efficient Isar Image Focusing Using the Discrete Gabor Representation in an Oversampling Scheme

Radar Imaging

Radar Imaging

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