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2018
Bistatic inverse synthetic aperture radar (B-ISAR) has progressed in the last decades pushed by technological advancements and by the need to overcome some limitations imposed by the monostatic radar geometry, as well as the need to image stealthy targets.
Martorella, Marco +3 more
openaire +3 more sources
Bistatic inverse synthetic aperture radar (B-ISAR) has progressed in the last decades pushed by technological advancements and by the need to overcome some limitations imposed by the monostatic radar geometry, as well as the need to image stealthy targets.
Martorella, Marco +3 more
openaire +3 more sources
Coherent multistatic ISAR imaging
IET International Conference on Radar Systems (Radar 2012), 2012This paper presents methods for Coherent Multistatic Radar Imaging for Non Cooperative Target Recognition (NCTR) with a network of radar sensors. Coherent Multistatic Radar Imaging is based on an extension of existing monostatic ISAR algorithms to the multistatic environment.
Dorp, Ph. van +2 more
openaire +2 more sources
2018
Passive radars (PRs) have drawn the attention of the scientific community for many decades, as they offer a number of advantages over conventional active radar systems [14, 9, 6, 10, 8, 16, 2, 7]. A passive radar is intrinsically a bistatic radar, since the transmitter and the receiver are not co-located.
Martorella, Marco +6 more
openaire +3 more sources
Passive radars (PRs) have drawn the attention of the scientific community for many decades, as they offer a number of advantages over conventional active radar systems [14, 9, 6, 10, 8, 16, 2, 7]. A passive radar is intrinsically a bistatic radar, since the transmitter and the receiver are not co-located.
Martorella, Marco +6 more
openaire +3 more sources
2014
Autofocus allows us to generate images with better quality by automatically adjusting the image focusing parameters. For radar imaging, autofocus means to automatically correct phase errors based on collected radar returns from targets. Inverse synthetic aperture radar (ISAR) motion compensation includes range alignment and phase adjustment.
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Autofocus allows us to generate images with better quality by automatically adjusting the image focusing parameters. For radar imaging, autofocus means to automatically correct phase errors based on collected radar returns from targets. Inverse synthetic aperture radar (ISAR) motion compensation includes range alignment and phase adjustment.
openaire +1 more source
2014
In this chapter, we will introduce the most commonly used ISAR range-Doppler image formation. However, if the Doppler spectrum generated by a rotating target has severe time variation, ISAR range-Doppler image will become smeared in the Doppler domain. In these cases, in addition to conventional rotational motion compensation (RMC) methods such as the ...
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In this chapter, we will introduce the most commonly used ISAR range-Doppler image formation. However, if the Doppler spectrum generated by a rotating target has severe time variation, ISAR range-Doppler image will become smeared in the Doppler domain. In these cases, in addition to conventional rotational motion compensation (RMC) methods such as the ...
openaire +1 more source
2014
As introduced in Chapter 3, inverse synthetic aperture radar (ISAR) data are arranged in a 2-D matrix, where the number of range cells is in its row and the number of pulses is in its column, or vice versa. To reconstruct an ISAR range-Doppler image, we first take range compression to obtain ISAR range profiles, which is a sequence of consecutive range
openaire +1 more source
As introduced in Chapter 3, inverse synthetic aperture radar (ISAR) data are arranged in a 2-D matrix, where the number of range cells is in its row and the number of pulses is in its column, or vice versa. To reconstruct an ISAR range-Doppler image, we first take range compression to obtain ISAR range profiles, which is a sequence of consecutive range
openaire +1 more source
Fast Sparse Aperture ISAR Autofocusing and Imaging via ADMM Based Sparse Bayesian Learning
IEEE Transactions on Image Processing, 2020Shuanghui Zhang, Yongxiang Liu
exaly