Automatic algorithm for inverse synthetic aperture radar images recognition and classification

Zeljković, V.; Li, Q.; Vincelette, R.; Tameze, Claude; Liu, F.

doi:10.1049/iet-rsn.2009.0112

Cited by 30 publications

(23 citation statements)

References 1 publication

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“…where the threshold t has been chosen according to the following [ (4) and k is a constant that depends on the image size-to-target ratio. Finally, the DRLSE method of [18] is applied to extract the target shape from the results of the modified SUSAN algorithm.…”

Section: Object Detectionmentioning

confidence: 99%

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Automatic Aircraft Target Recognition by ISAR Image Processing based on Neural Classifier

Benedetto¹,

Fulginei²,

Laudani³

et al. 2012

IJACSA

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Abstract-This work proposes a new automatic target classifier, based on a combined neural networks' system, by ISAR image processing. The novelty introduced in our work is twofold. We first present a novel automatic classification procedure, and then we discuss an improved multimedia processing of ISAR images for automatic object detection. The classifier, composed by a combination of 20 feed-forward artificial neural networks, is used to recognize aircraft targets extracted from ISAR images. A multimedia processing by two recently introduced image processing techniques is exploited to improve the shape and features extraction process. Performance analysis is carried out in comparison with conventional multimedia techniques and standard detectors. Numerical results obtained from wide simulation trials evidence the efficiency of the proposed method for the application to automatic aircraft target recognition.

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Section: Object Detectionmentioning

confidence: 99%

“…In the last years, many methods of ISAR ATR techniques have been developed in the open literature. Before detecting an object, the image is first segmented and then the object is recognized [4]- [5]. Image segmentation is the process of partitioning/subdividing a digital image into multiple meaningful regions.…”

Section: Introductionmentioning

confidence: 99%

Automatic Aircraft Target Recognition by ISAR Image Processing based on Neural Classifier

Benedetto¹,

Fulginei²,

Laudani³

et al. 2012

IJACSA

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“…Since high resolution range profile (HRRP) and ISAR image reflect structure of target precisely, they are widely used in missile defense and target recognition [1][2][3][4]. We usually increase bandwidth to gain high range resolution by improving hardware in traditional radar systems, which faces limitation such as high cost, difficulties in design and manufacturing, maximum performance of single-band radar.…”

Section: Introductionmentioning

confidence: 99%

Sparse subband fusion imaging based on parameter estimation of geometrical theory of diffraction model

Tian

Chen

2014

IET Radar, Sonar & Navigation

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This study focuses on sparse subband fusion imaging. A method based on high-precision parameter estimation of geometrical theory of diffraction (GTD) model is given. Considering the incoherence problem in each subband data, a coherent processing method is adopted in the paper. Based on an all-pole model, it makes use of the phase difference of pole and scattering coefficient between each sub-band to effectively estimate the incoherent components. After coherent processing, the high and low frequency subband data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation algorithm is adopted to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data with fixed-points indicate that the resolution of onedimensional (1D) range profile and 2D inverse synthetic aperture radar (ISAR) image based on this method is better than that of each sub-band. In this way, the validity of the proposed method is proved.

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“…Inverse synthetic aperture radar (ISAR) [1][2][3][4] can generate 2D high-resolution images of non-cooperative targets from a long distance, which can be used for military and civilian purposes. The ISAR image may result in the loss of structural information since it is just the Range-Doppler plane projection of a spatial three-dimensional target.…”

Section: Introductionmentioning

confidence: 99%

Interferometric ISAR imaging for space moving targets on a squint model using two antennas

Tian

Liu

Tang

et al. 2014

Journal of Electromagnetic Waves and Applications

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This paper proposes a novel InISAR imaging method for space moving targets on a squint model using two antennas. In the pre-processing for range compression based on wideband direct sampling data, an adaptive matched filter containing speed is designed to carry out high-speed movement compensation that is essential for space targets. In order to reserve the phase history of each antenna, coherent processing for ISAR imaging is adopted. The corresponding size can be achieved by interferometric processing of the two complex ISAR images. Considering the condition may not be strictly satisfied, the influence of 3D motion and squint model is analyzed and a compensation method is adopted. Image distortion is corrected using coordinate transform. Simulation results confirm the effectiveness of the analysis and 3D imaging algorithm.

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Automatic algorithm for inverse synthetic aperture radar images recognition and classification

Cited by 30 publications

References 1 publication

Automatic Aircraft Target Recognition by ISAR Image Processing based on Neural Classifier

Automatic Aircraft Target Recognition by ISAR Image Processing based on Neural Classifier

Sparse subband fusion imaging based on parameter estimation of geometrical theory of diffraction model

Interferometric ISAR imaging for space moving targets on a squint model using two antennas

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