Application of adaptive joint time–frequency algorithm for focusing distorted ISAR images from simulated and measured radar data

Thayaparan, T.; Λαμπρόπουλος, Γεώργιος; Wong, S.K.; Riseborough, E.

doi:10.1049/ip-rsn:20030670

Cited by 65 publications

(39 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The positions of the radar array and the imaging region satisfy property 1. The transmitting signals used for simulation are denoted in (8). In consideration of noise impact in practical experiments, the imaging equation is rewritten as Sr = S · σ + n, where n is modeled as white noise.…”

Section: Results Using Phantomsmentioning

confidence: 99%

“…The noncooperative motion yields time-varying Doppler frequency which destroys the Fourier-based imaging formation and would badly blur the images beyond recognition [6]. A long CIT (or a large aspect-angle integration) indeed provides the desired resolution, but meanwhile the nonuniform space sampling will produce smeared images which are difficult to be refocused even though various motion compensation algorithms are applied [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Three Dimensional Radar Coincidence Imaging

Li¹,

Li²,

Cheng³

et al. 2013

PIER M

View full text Add to dashboard Cite

Abstract-Two dimensional (2D) radar coincidence imaging is an instantaneous imaging technique which can obtain 2D focused highresolution images using a single pulse without the limitation to the target relative motions. This paper extends the imaging method to three dimensions. Such a three-dimensional (3D) radar imaging technique does not rely on Doppler frequency for resolution and has an extremely short imaging time (shorter than a pulse width), resulting in two remarkable properties: 1) it does not require the relative rotation between targets and radar; 2) it can considerably avoid the image blurring in processing noncooperative targets without motion compensation. 3D radar coincidence imaging consequently can derive high-quality images for either the targets that are stationary with respect to radars or the ones in maneuvering 3D rotations. The validity of the proposed imaging technique is confirmed by numerical simulations.

show abstract

Section: Results Using Phantomsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Three Dimensional Radar Coincidence Imaging

Li¹,

Li²,

Cheng³

et al. 2013

PIER M

View full text Add to dashboard Cite

show abstract

“…On the other hand, micro-Doppler features can be regarded as a unique signature of an object with movements, providing additional information for the classification, recognition, and identification of the object. Some methods for separation of the m-D effect or extract the m-D features from the radar echoes are proposed [10,[18][19][20][21]. Thus, the micro-motion dynamics can be used in the countermeasures of ISAR which may decrease the readability of radar images or make the separation and extraction of m-D signatures difficult and spurious.…”

Section: Introductionmentioning

confidence: 99%

Rotational Micro-Motion Modulated Jamming for Countering Isar Based on Intermittent Sampling Repeater

Pan¹,

Wang²,

Feng³

et al. 2013

PIER C

View full text Add to dashboard Cite

Abstract-The intermittent sampling repeater jamming (ISRJ) can only produce fake point scatterers in the down-range, while the timevarying frequency induced by rotational micro-motion dynamics blurs the image in the cross-range. This paper focuses on the combination of the above two methods to counter the inverse synthetic aperture radar (ISAR). Based on the signal models of coherent ISAR signal processing, principles of the jamming are derived. The key jamming parameters and the selection criteria are determined by two steps. Finally, the validity of the proposed algorithm is demonstrated using the numeric simulations and simulations based on the measured data.

show abstract

“…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%

“…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%

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

Park¹,

Myung²

2013

PIER

View full text Add to dashboard Cite

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.

show abstract

Application of adaptive joint time–frequency algorithm for focusing distorted ISAR images from simulated and measured radar data

Cited by 65 publications

References 13 publications

Three Dimensional Radar Coincidence Imaging

Three Dimensional Radar Coincidence Imaging

Rotational Micro-Motion Modulated Jamming for Countering Isar Based on Intermittent Sampling Repeater

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

Contact Info

Product

Resources

About