Passive GNSS-Based Multistatic SAR: First Experimental Results

Nithirochananont, Ussanai; Antoniou, Michail; Cherniakov, M.

doi:10.23919/irs.2018.8448265

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…However, these mentioned researches are only for bistatic configuration with a single satellite transmitter. To take full advantage of GNSS, the availability of multiple navigation satellites is exploited in [21] and [22]. The bistatic images concerning different satellites are generated separately, followed by the multistatic image formation by noncoherently combining the bistatic images.…”

Section: Introductionmentioning

confidence: 99%

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation

Huang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In terms of the global coverage provided by global navigation satellite system (GNSS) signals, radar images of a large field-of-view can be obtained via passive synthetic aperture radar (SAR) using these signals of opportunity. Usually, large field-ofview imaging is challenging using conventional SAR methods owing to the space-variant resolution. In addition, only a moderate range resolution can be provided by the GNSS transmitters in the passive SAR system. In this paper, an optimal imaging method for a large field-of-view using GNSS-based passive SAR is proposed, which exploits the inherent multistatic nature of GNSS. At first, the spatial resolution of each scatterer in the observation area relative to each GNSS transmitter is calculated according to the geometry. Then, the selection of the transmitter set is modeled as an optimization problem, where the minimal resolution cell is used as the optimal criterion. After that, an evolutionary algorithm is applied to solve the optimization problem. Finally, the space-time combination of the echoes over a long dwell time concerning selected GNSS transmitters is performed to form the radar image with a minimal spatial resolution. The proposed method is extensively validated using two experimental datasets, where the passive radar consists of BeiDou satellites and a fixed receiver. The spatial resolution improvement and the large field-of-view imaging capability of the proposed method are forcefully demonstrated according to the experimental results.

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Section: Introductionmentioning

confidence: 99%

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation

Huang

et al. 2022

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…Another aspect of GNSS-based remote sensing relies on passive radar techniques. One of the most well established GNSS-based radar technologies is the passive Synthetic Aperture Radar (SAR) [6], which has been considered to map fixed objects on land and to monitor temporal land changes and deformations [7]- [10], while also exploiting spatial diversity to improve the quality of the output products [11]- [14]. Moreover, detection of moving targets has been addressed, [15], particularly for air targets such as airplanes and helicopters by considering forward-scattering radar modes [16]- [19].…”

Section: Introductionmentioning

confidence: 99%

Passive Radar Imaging of Ship Targets With GNSS Signals of Opportunity

Pastina

Santi

Pieralice

et al. 2021

IEEE Trans. Geosci. Remote Sensing

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Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document.When citing, please reference the published version. Take down policyWhile the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

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“…Extracting targets information using CLEAN technique before fusion processing and fusing multistatic images before targets information extraction were both testified, resulting in enhanced image information space and improved image performance respectively. In 2018, Nithirochananont et al [33] investigated multistatic GNSS-based imaging using two different constellations of GNSS satellites, GPS and Galileo. Non-coherent addition was applied on the bistatic images, and targets geometric features were revealed including edge, shape and dimensions.…”

Section: Introductionmentioning

confidence: 99%

An Image Formation Algorithm for Bistatic SAR Using GNSS Signal With Improved Range Resolution

et al. 2020

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Passive synthetic aperture radar (SAR) using Global Navigation Satellite System (GNSS) signals as the illuminators of opportunity has a relative coarse range resolution due to the narrow bandwidth of the navigation signals and the bi-static acquisition geometry, limiting its application for high-resolution requirement. In this paper, an image formation algorithm for range resolution improvement is investigated. A modified second order differentiation based method is applied on the range compressed signal of reference channel and surveillance channel, improving range resolution and keeping side-lobes at a lower level simultaneously, and the phase of processed signal is preserved by phase multiplication compensation for the following azimuth compression processing. To validate the effectiveness and benefits of the proposed algorithm in terms of range resolution and targets side-lobes, point targets simulation under different situations and real field experiment with strong scatters are conducted and discussed. Compared with the traditional GNSS-based passive SAR imaging algorithm, the results of the proposed method show that the imaging performance can be improved for better range resolution and lower side-lobes, benefitting for better distinguishing nearby targets and recognizing weak targets.

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Passive GNSS-Based Multistatic SAR: First Experimental Results

Cited by 4 publications

References 15 publications

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation

Passive Radar Imaging of Ship Targets With GNSS Signals of Opportunity

An Image Formation Algorithm for Bistatic SAR Using GNSS Signal With Improved Range Resolution

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