GNSS-Based SAR Interferometry for 3-D Deformation Retrieval: Algorithms and Feasibility Study

Liu, Feifeng; Fan, Xuezhen; Zhang, Tian; Liu, Quanhua

doi:10.1109/tgrs.2018.2825220

Cited by 35 publications

(25 citation statements)

References 31 publications

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“…12 shows the bistatic multi-frame RD maps obtained by the non-coherent integration of the first N = 10 frames by applying the TMC (and skipping in this case the MSC) and selecting the branch of the Doppler rate bank providing the highest SNR in the area where the ferries are located. Particularly, the highest SNR is reached on the same branch for the two ferries: this is in agreement with the recorded AIS information stating that the Doppler rate difference between the two targets was lower than the step in (15). In Fig.…”

Section: A Scenario 1: River Shippingsupporting

confidence: 90%

“…One of the most well-established GNSS-based radar technologies is the passive Synthetic Aperture Radar (SAR), which has been investigated at both theoretical and practical levels considering different kinds of configurations, comprising ground-based or airborne receivers and bistatic or multistatic geometries [7]- [15]. Moreover, detection of moving targets has been addressed, particularly for air targets such as airplanes and helicopters by considering forward-scattering radar modes [16]- [18].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint Detection and Localization of Vessels at Sea With a GNSS-Based Multistatic Radar

Santi

Pieralice

Pastina

2019

IEEE Trans. Geosci. Remote Sensing

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This paper addresses the exploitation of GNSS as opportunistic sources for the joint detection and localization of vessels at sea in a passive multistatic radar system. A single receiver mounted on a proper platform (e.g., a moored buoy) can collect the signals emitted by multiple navigation satellites and reflected from ship targets of interest. This paper puts forward a single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration. A proper strategy is defined to form a long-time and multistatic range&Doppler (RD) map, where the total target power can be reinforced with respect to, in turn, the case in which the RD map is obtained over as a short dwell and the case in which a single transmitter is employed. The exploitation of both the long integration time and the multiple transmitters can greatly enhance the performance of the system, allowing counteracting the low power budget provided by the considered sources representing the main bottleneck of this technology. Moreover, the proposed singlestage approach can reach superior detection performance than a conventional two-stage process where peripheral decisions are taken at each bistatic link and subsequently the localization is achieved by multilateration methods. Theoretical and simulated performance analysis is proposed and also validated by means of experimental results considering Galileo transmitters and different types of targets of opportunity in different scenarios. Obtained results prove the effectiveness of the proposed method to provide detection and localization of ship targets of interest.

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Section: A Scenario 1: River Shippingsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Joint Detection and Localization of Vessels at Sea With a GNSS-Based Multistatic Radar

Santi

Pieralice

Pastina

2019

IEEE Trans. Geosci. Remote Sensing

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“…GNSS-R Bi-static Synthetic Aperture Radar (BSAR) is one of the new applications of the GNSS-R [15][16][17][18][19][20][21][22][23][24][25]. It uses the GNSS signal as a non-cooperative illuminator to obtain an image of the Earth's surface.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, commonly used imaging algorithms for GNSS-R BSAR are usually based on the Back-Projection Algorithm (BPA) [15][16][17][18][19][20][21][22][23]. Although having the ability of handling different configurations, these algorithms are very time consuming.…”

mentioning

confidence: 99%

An Efficient Imaging Algorithm for GNSS-R Bi-Static SAR

et al. 2019

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Global Navigation Satellite System Reflectometry (GNSS-R) based Bi-static Synthetic Aperture Radar (BSAR) is becoming more and more important in remote sensing, given its low power, low mass, low cost, and real-time global coverage capability. Due to its complex configuration, the imaging for GNSS-R BSAR is usually based on the Back-Projection Algorithm (BPA), which is very time consuming. In this paper, an efficient and general imaging algorithm for GNSS-R BSAR is presented. A Two Step Range Cell Migration (TSRCM) correction is firstly applied. The first step roughly compensates the RCM and Doppler phase caused by the motion of the transmitter, which simplifies the SAR data into the quasi-mono-static case. The second step removes the residual RCM caused by the motion of the receiver using the modified frequency scaling algorithm. Then, a cubic phase perturbation operation is introduced to equalize the Doppler frequency modulation rate along the same range cell. Finally, azimuth phase compensation and geometric correction are completed to obtain the focused SAR image. A simulation and experiment are conducted to demonstrate the feasibility of the proposed algorithm, showing that the proposed algorithm is more efficient than the BPA, without causing significant degradation in imaging quality.

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“…However, extreme attitude control is required for this method to change the incidence angle of the antenna, which is difficult for satellites with large antennas. Another method is to change the heading angle of the satellite and make it deviate from the North-South direction, which can fundamentally solve the problem of low precision of deformation estimation in the north component [14,15], whereas the satellite heading angle is directly related to the orbital inclination of the satellite, and the non-polar orbit will limit the imaging coverage in the latitudinal direction.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Three-Dimensional Surface Deformation Using an Improved Differential SAR Tomography System

Wang

Liu

2019

Electronics

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Conventional differential synthetic aperture radar tomography (D-TomoSAR) can only capture the scatterers’ one-dimensional (1-D) deformation information along the line of sight (LOS) of the synthetic aperture radar (SAR), which means that it cannot retrieve the three-dimensional (3-D) movements of the ground surface. To retrieve the 3-D deformation displacements, several methods have been proposed; the performance is limited due to the insufficient sensitivity for retrieving the North-South motion component. In this paper, an improved D-TomoSAR model is established by introducing the scatterers’ 3-D deformation parameters in slant range, azimuth, and elevation directions into the traditional D-TomoSAR model. The improved D-TomoSAR can be regarded as a multi-component two-dimensional (2-D) polynomial phase signal (PPS). Then, an effective algorithm is proposed to retrieve the 3-D deformation parameters of the ground surface by the 2-D product high-order ambiguity function (PHAF) with the relax (RELAX) algorithm. The estimation performance is investigated and compared with the traditional algorithm. Simulations and experimental results with semi-real data verify the effectiveness of the proposed signal model and algorithm.

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GNSS-Based SAR Interferometry for 3-D Deformation Retrieval: Algorithms and Feasibility Study

Cited by 35 publications

References 31 publications

Joint Detection and Localization of Vessels at Sea With a GNSS-Based Multistatic Radar

Joint Detection and Localization of Vessels at Sea With a GNSS-Based Multistatic Radar

An Efficient Imaging Algorithm for GNSS-R Bi-Static SAR

Retrieval of Three-Dimensional Surface Deformation Using an Improved Differential SAR Tomography System

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