Airborne high-resolution isar imaging of ship targets at sea

Hajduch, Guillaume; Caillec, J.-M. Le

doi:10.1109/taes.2004.1292177

Cited by 68 publications

(21 citation statements)

References 12 publications

(11 reference statements)

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“…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%

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: Introductionmentioning

confidence: 99%

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

Park¹,

Myung²

2013

PIER

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“…This study focuses on the radar recognition of ships. Traditionally, the SAR (synthetic aperture radar) or ISAR (inverse synthetic aperture radar) images are usually utilized to recognize the ship targets, e.g., [1,2]. However, it is usually expensive or even difficult to obtain such SAR or ISAR images.…”

Section: Introductionmentioning

confidence: 99%

Application of Ica Technique to Pca Based Radar Target Recognition

Huang¹,

Lee²

2010

PIER

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Abstract-In this paper, the ICA (independent component analysis) technique is applied to PCA (principal component analysis) based radar target recognition. The goal is to identify the similarity between the unknown and known targets. The RCS (radar cross section) signals are collected and then processed to serve as the features for target recognition. Initially, the RCS data from targets are collected by angular-diversity technique, i.e., are observed in directions of different elevation and azimuth angles. These RCS data are first processed by the PCA technique to reduce noise, and then further processed by the ICA technique for reliable discrimination. Finally, the identification of targets will be performed by comparing features in the ICA space. The noise effects are also taken into consideration in this study. Simulation results show that the recognition scheme with ICA processing has better ability to discriminate features and to tolerate noises than those without ICA processing. The ICA technique is inherently an approach of high-order statistics and can extract much important information about radar target recognition. This property will make the proposed recognition scheme accurate and reliable. This study will be helpful to many applications of radar target recognition.

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“…Radar target recognition [1][2][3] means to identify targets or achieve the fundamental information of targets by received electromagnetic signals. In practical measurement, the received signals contain a lot of random noises in addition to the clean signals.…”

Section: Introductionmentioning

confidence: 99%

Application of SVD Noise-Reduction Technique to Pca Based Radar Target Recognition

Lee¹,

Ou²,

Fang³

2008

PIER

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Abstract-The noise effect is very challenging in radar target recognition. It usually degrades the accuracy of target recognition and then makes the recognition unreliable. In this study, we present a noise-reduction technique to improve the accuracy of radar target recognition. Our noise-reduction technique is based on the SVD (singular value decomposition). The PCA (principal components analysis) based radar recognition algorithm is utilized to verify our noise-reduction scheme. In our treatment, the received signals are arranged into a Hankel-form matrix. This Hankel-form matrix is decomposed into two subspaces, i.e., the noise-related subspace and clean-signal subspace. The noise reduction is obtained by suppressing the noise-related subspace and retaining the clean-signal space only. Simulation results show that the accuracy of target recognition is greatly improved as the received signals are first processed by the SVD noise-reduction technique. With the use of proposed noise-reduction scheme, the radar target recognition can tolerate more noises and then becomes more reliable. The noise-reduction technique in this study can also be applied to many other problems in radar engineering.

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Airborne high-resolution isar imaging of ship targets at sea

Cited by 68 publications

References 12 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

Application of Ica Technique to Pca Based Radar Target Recognition

Application of SVD Noise-Reduction Technique to Pca Based Radar Target Recognition

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