Resource allocation for target tracking in multiple radar architectures over lossy networks

Zuo, Lei; Hu, Juan; Sun, Han‐Dong; Gao, Yun

doi:10.1016/j.sigpro.2023.108973

Cited by 15 publications

(2 citation statements)

References 38 publications

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“…The synthetic aperture radar (SAR) plays a significant role in various fields, including land and resources, earthquake, mapping, environment, disaster monitoring, and forestry [1]. Additionally, the inverse synthetic aperture radar (ISAR) is a radar imaging system capable of acquiring high-resolution images of moving targets [2][3][4][5][6][7]. Parameter estimation and motion compensation are key techniques in ISAR imaging [8,9].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets

Zhang,

Xu,

et al. 2023

Remote Sensing

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As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to overlapping phenomena in the Doppler history. Therefore, for situations in which ship formation targets with little difference in motion parameters are included in the same radar beam, this paper proposes a multi-domain joint ISAR separation imaging method for multi-ship targets. First, the method performs echo separation using the Hough transform (HT) with the minimum entropy autofocus method in the image domain. Secondly, the time–frequency curve is extracted in the time–frequency domain using the short-time Fourier transform (STFT) for time–frequency analysis, which solves the problem of the ship formation targets being aliased on both echo and Doppler history after range compression and achieves the purpose of separating the echo signals of the sub-ship targets with high accuracy. Eventually, better-focused images of each target are obtained via further motion compensation and precise imaging. Finally, the effectiveness of the proposed method is verified using a simulation and measured data.

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Section: Introductionmentioning

confidence: 99%

A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets

Zhang,

Xu,

et al. 2023

Remote Sensing

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“…Introduction: Multiple-input multiple-output (MIMO) radars have attracted more attentions due to its remarkable advantages over phasedbased radar [1][2][3][4][5], such as high spatial resolution, accurate target detection and strong interference suppression. The performance benefits of MIMO radar come from the transmitting and receiving multiple orthogonal signals, and larger virtual array.…”

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confidence: 99%

A robust beamforming for MIMO radar against virtual array steering vector mismatch

Gao

Jing

Liao

et al. 2023

Electronics Letters

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This letter considers the problem of beamforming in multiple-input multiple-output (MIMO) radar. The mismatch phenomenon of MIMO radar virtual array steering vector is addressed, which can better describe the mismatch characteristics of not only one-way transmitting or receiving path but also the whole transmit-receive path for a collocated MIMO radar. Then, a new robust beamforming method for MIMO radar against virtual array steering vector mismatch is proposed. The object function of this robust MIMO radar beamformer is constructed from an infinite norm of the output data, which is solved by linear programming. The performance of the proposed beamformer is verified by simulation results. Numerical results illustrate that proposed beamformer exhibits good performance improvement in virtual array steering vector mismatch compared to conventional methods.

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