A Multistatic GNSS Synthetic Aperture Radar for Surface Characterization

Lindgren, Tore; Akos, Dennis

doi:10.1109/tgrs.2008.917268

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…Many research studies had focused on the relationship of reflected satellite signal intensity and geometry structure [22]- [24]. However, little attention has been devoted to the scattering mechanism in GNSS-BSAR images.…”

Section: B Feature Analysis Of Single-angle Imagesmentioning

confidence: 99%

Multiangle BSAR Imaging Based on BeiDou-2 Navigation Satellite System: Experiments and Preliminary Results

Zeng

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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This paper analyzes the multiangle imaging results for bistatic synthetic aperture radar (BSAR) based on global navigation satellite systems (GNSS-BSAR). Due to the shortcoming of GNSS-BSAR images, a multiangle observation and data processing strategy based on BeiDou-2 navigation satellites was put forward to improve the quality of images and the value of system application. Twenty-six BSAR experiments were conducted and analyzed in different configurations. Furthermore, a region-based fusion algorithm using region-of-interest (ROI) segmentation was proposed to generate a high-quality fusion image. Based on the fusion image, typical targets such as water area, vegetation area, and artificial targets were compared and interpreted among single/ multiple-angle images. The results reveal that the multiangle imaging method was a good technique to enhance image information, which might extend the applications of GNSS-BSAR.Index Terms-Bistatic synthetic aperture radar (BSAR), global navigation satellite system (GNSS), image fusion, image interpretation, multiangle.

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Section: B Feature Analysis Of Single-angle Imagesmentioning

confidence: 99%

Multiangle BSAR Imaging Based on BeiDou-2 Navigation Satellite System: Experiments and Preliminary Results

Zeng

et al. 2015

IEEE Trans. Geosci. Remote Sensing

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“…Except for repeated acoustic/mechanic wave-propagation measurements under temperature and/or pressure variations, other applicable non-stationary measurement situations describable by (1) include: repeated flow measurements in turbulent conditions [10]; sedimentation measurements in suspensions or slurries in the presence of flocs and bubbles [11]; repeated GNSS/GPS measurements under varying ionospheric [12,13] and/or multipath conditions [14] (where (1) can be used to describe either the correlation sequence [15] or the measured waveforms directly [16], depending on the SNR conditions).…”

Section: The Signal Modelmentioning

confidence: 99%

Compensating distortion effects in repeated measurements under non-stationary conditions

Martinsson¹

2008

Meas. Sci. Technol.

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In this paper a compensation technique is presented for applications using repeated measurements under moderate non-stationary measurement conditions. The assumption is that the measurement conditions are stationary during a single repeated measurement but non-stationary over the entire measurement time. The objective with repeated measurements is often to retrieve an estimate of the (noise reduced) signal and its uncertainties. In order to obtain accurate estimates of these two quantities, stationary measurement conditions must be guaranteed under the measurement time. A condition that in many situations is difficult to achieve, e.g., during long measurement times or in a rapidly changing environment. The proposed method compensates for linear dynamic changes during the measurement time, where the dynamical changes, the underlying signal waveform and the noise covariance are considered unknown. The theoretical effect of moderate non-stationary conditions on repeated measurements is analyzed and experimentally validated. Estimation results using the proposed technique are presented for repeated ultrasonic measurements under non-stationary temperature conditions. The results show accurate signal estimation and noise characterization with uncorrelated normally distributed residuals, in contrast to standard synchronization techniques.

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“…From this point of view, GNSS are an ideal choice: a single constellation guarantees that 6-8 satellites are simultaneously in visibility over the horizon, and this number can be increased up to 32 when all the GNSS are fully operational. All of these signals can be received and processed separately or jointly by a stationary ground-based receiver, essentially forming a passive multistatic radar system [5][6][7][8]. In our latest research [6] it was shown that the incoherent addition of the individual bistatic ambiguity functions obtained by multiple, spatially separated GNSS transmitters can yield multistatic imagery that may essentially enhance spatial resolution with respect to the individual images.…”

Section: Introductionmentioning

confidence: 99%

Passive multistatic SAR with GNSS transmitters and using joint bi/multi-static CLEAN technique

Santi

Bucciarelli

Pastina

et al. 2016

2016 IEEE Radar Conference (RadarConf)

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This paper explores the capability of GNSS as opportunity transmitters for passive multistatic SAR. The large number of navigation satellites illuminating the same area from multiple view angles enables a single ground-based stationary receiver to combine the individual bistatic images thus achieving multistatic imagery capability with improved spatial resolution. Nevertheless, such a technique introduces artifacts corrupting the quality of the image information space. In this paper, a joint bi/multi-static CLEAN algorithm is exploited in order to correctly recovering the information of the scene. An experimental study is therefore presented, demonstrating the potential of this technology to extract detailed information of an area for persistent monitoring purposes.

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A Multistatic GNSS Synthetic Aperture Radar for Surface Characterization

Cited by 11 publications

References 9 publications

Multiangle BSAR Imaging Based on BeiDou-2 Navigation Satellite System: Experiments and Preliminary Results

Multiangle BSAR Imaging Based on BeiDou-2 Navigation Satellite System: Experiments and Preliminary Results

Compensating distortion effects in repeated measurements under non-stationary conditions

Passive multistatic SAR with GNSS transmitters and using joint bi/multi-static CLEAN technique

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