Taking a Look Beneath the Surface: Multicopter UAV-Based Ground-Penetrating Imaging Radars

Grathwohl, Alexander; Stelzig, Michael; Kanz, Julian; Fenske, Patrick; Benedikter, Andreas; Knill, Christina; Ullmann, Ingrid; Hajnsek, Irena; Moreira, Alberto; Krieger, Gerhard; Vossiek, Martin; Waldschmidt, Christian

doi:10.1109/mmm.2022.3188126

Cited by 15 publications

(7 citation statements)

References 104 publications

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“…This allows one radar to evaluate the signal from another radar within the network without the performance being affected by effects like uncorrelated phase noise. By this way, a radar network can enable multistatic synthetic aperture radar (SAR) [8], [10], [11], [12] as well as network-based direction of arrival (DoA) estimation [9], [13], [14]. Different synchronization strategies have been proposed for radar networks.…”

Section: Introductionmentioning

confidence: 99%

On the Synchronization of Uncoupled Multistatic PMCW Radars

Werbunat,

Aguilar,

Almarashly

et al. 2024

IEEE Trans. Microwave Theory Techn.

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Radar networks and multistatic synthetic aperture radars (SARs) allow overcoming the limitations of single radar sensors. However, a good synchronization of the radar sensors is crucial to avoid performance loss due to phase noise and frequency offsets. While this is usually done via cables or dedicated synchronization signals, digital radars allow for new techniques. This work proposes a new concept for the synchronization of phase-modulated continuous wave (PMCW) radars. The synchronization is performed solely by digital signal processing on the receiver side, adapting techniques known from digital communications. It mitigates effects caused by incoherency, which are phase noise, carrier frequency offsets and phase deviations of the local oscillator (LO), and sampling frequency offsets. At first, the impact of these effects is mathematically derived and analyzed in detail. Then, the proposed synchronization concept is presented, and its performance is thoroughly evaluated. Very good results are obtained not only in simulations but also in measurements with a 77-GHz radar demonstrator.

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Section: Introductionmentioning

confidence: 99%

On the Synchronization of Uncoupled Multistatic PMCW Radars

Werbunat,

Aguilar,

Almarashly

et al. 2024

IEEE Trans. Microwave Theory Techn.

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“…This allows UAVs to operate in hard-to-reach areas or over difficult terrain. Finally, the ability of UAVs to carry additional payload like sensor systems enabled various new application areas such as radar remote sensing [1]- [3]. Taking the platform motion into account, UAV-based radar systems are especially interesting for highresolution synthetic aperture radar (SAR) imaging.…”

Section: Introductionmentioning

confidence: 99%

“…Today, SAR systems play a key role in various space remote sensing applications such as surveillance, geoscience, environmental research, mapping or earth observation [4]. UAV-based SAR systems are demonstrated to be applicable for sub-surface imaging [3], interferometry, or to generate digital elevation models [5]. They are also considered very promising candidates for various civil and environmental applications, such as short and long-term monitoring of agriculture, biomass, or analyzing the impact of the climate change on nature.…”

Section: Introductionmentioning

confidence: 99%

Improving SAR Imaging by Superpixel-Based Compressed Sensing and Backprojection Processing

Bonfert,

Ruopp,

Waldschmidt

2024

IEEE Trans. Geosci. Remote Sensing

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Radars mounted on unmanned aerial vehicles (UAVs) enable a high flexibility on data acquisition since arbitrary and especially non-linear flight trajectories can be achieved. Compared to linear flight trajectories, non-linear trajectories achieve better image quality and allow the scene and targets to be observed from different angles, thereby capturing angledependent features. However, inversion of synthetic aperture radar (SAR) data for non-linear apertures and sample acquisition is computationally taxing and artifacts may arise in the image due to the aperture's structure. In order to suppress aperture artifacts and clutter in the SAR image, a backprojection imaging algorithm combined with compressed sensing methods is proposed. In this work, an efficient way to calculate the backprojection in a compressed sensing framework is described that does not require interpolation steps. Since SAR images are neither strictly sparse nor noise dominated, an adapted compressed sensing algorithm is proposed that accounts for clutter and extended targets which are spread across multiple image pixels. In addition, an image segmentation approach is presented that enables faster processing while being robust to extended targets located at segment edges. With the proposed approach, SAR images of arbitrary flight paths can be processed efficiently with fewer acquisition points while achieving better clutter suppression at the same image quality compared to equally dense measurement sets.

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“…On the other hand, in multi/bistatic radar, where the network scale is smaller, synchronization accuracy takes precedence. To enhance accuracy, the bistatic SAR satellites [17][18][19] adopt a time division and co-frequency method to exchange pulse signals, achieving time and phase synchronization between two satellites. Building upon this, some studies in the literature have designed multi-node wireless synchronization protocol [11,12,20], improving the efficiency of a two-way time transfer for wireless nodes via time division broadcasting.…”

Section: Introductionmentioning

confidence: 99%

High-Precision Time Difference of Arrival Estimation Method Based on Phase Measurement

Xin,

Ge,

Zhang

et al. 2024

Remote Sensing

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In unmanned aerial vehicle (UAV)-based time difference of arrival (TDOA) positioning technique, baselines are limited due to communication constraints. In this case, the accuracy is highly sensitive to the TDOA measurements’ error. This article primarily addresses the problem of short-baseline high-precision time synchronization and TDOA measurement. We conducted a detailed analysis of error models in TDOA systems, considering both the time and phase measurement. We utilize the frequency division wireless phase synchronization technique in TDOA systems. Building upon this synchronization scheme, we propose a novel time delay estimation method that relies on phase measurements based on the integer least squares method. The performance of this method is demonstrated through Monte Carlo simulations and outdoor experiments. The standard deviations of synchronization and TDOA measurements in experiments are 1.12 ps and 1.66 ps, respectively. Furthermore, the circular error probable (CEP) accuracy is improved from 0.33%R to 0.02%R, offering support for the practical application of distributed short-baseline high-precision passive location techniques.

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Taking a Look Beneath the Surface: Multicopter UAV-Based Ground-Penetrating Imaging Radars

Cited by 15 publications

References 104 publications

On the Synchronization of Uncoupled Multistatic PMCW Radars

On the Synchronization of Uncoupled Multistatic PMCW Radars

Improving SAR Imaging by Superpixel-Based Compressed Sensing and Backprojection Processing

High-Precision Time Difference of Arrival Estimation Method Based on Phase Measurement

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