High resolution subsurface imaging of deep targets based on distributed sensor networks

Dagefu, Fikadu T.; Sarabandi, Kamal

doi:10.1109/igarss.2009.5418057

Cited by 5 publications

(2 citation statements)

References 7 publications

(6 reference statements)

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“…Penetration is improved at longer wavelengths, although this generally leads to a loss of imaging resolution so there is a tradeoff with using lower frequencies. However, wideband VHF waveforms can be used for imaging, using measurements from multiple locations [102]- [105].…”

Section: Time Of Arrival Based Geolocationmentioning

confidence: 99%

Low Frequency Multi-Robot Networking

Sadler,

Dagefu,

Twigg

et al. 2024

IEEE Access

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Autonomous teams of unmanned ground and air vehicles rely on networking and distributed processing to collaborate as they jointly localize, explore, map, and learn in sometimes difficult and adverse conditions. Co-designed intelligent wireless networks are needed for these autonomous mobile agents for applications including disaster response, logistics and transportation, supplementing cellular networks, and agricultural and environmental monitoring. In this paper we describe recent progress on wireless networking and distributed processing for autonomous systems using a low frequency portion of the electromagnetic spectrum, here defined as roughly 25 to 100 MHz with corresponding wavelengths of 3 to 12 meters. This research is motivated by the desire to support autonomous systems operating in dense and cluttered environments by harnessing low frequency propagation, where meters long wavelengths yield significantly reduced scattering and enhanced penetration of obstacles and structures. This differs considerably from higher frequency propagation, requiring different low frequency propagation models than those widely employed for other bands. Progress in use of low frequency for autonomous systems has resulted from combined advances in low frequency propagation modeling, networking, antennas and electromagnetics, geolocation, multi-antenna array distributed beamforming, and mobile collaborative processing. This article describes the breadth and the depth of interaction between areas, leading to new tools and methods, especially in physically complex indoor/outdoor, dense urban, and other challenging scenarios. We bring together key results, models, measurements, and experiments that describe the state of the art for new uses of low frequency spectrum for multi-agent autonomy.

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Section: Time Of Arrival Based Geolocationmentioning

confidence: 99%

Low Frequency Multi-Robot Networking

Sadler,

Dagefu,

Twigg

et al. 2024

IEEE Access

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“…Optical imaging plays a significant role in observing defects in objects [1][2][3][4][5]. Its main advantage lies in its broad observation spectrum characteristics and high resolution.…”

Section: Introductionmentioning

confidence: 99%

Photoacoustic Tomography System for Roughly Painted Micro Objects

Setiawan

Setiaji

Dewantoro

et al. 2019

J Electromagn Eng Sci

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Subsurface imaging is challenging; it is difficult to detect objects visually. In this research, a novel non-contact photoacoustic (PA) imaging system was developed to detect subsurface objects. The Rosencwaig-Gersho (RG) model was successfully employed to capture microobject images covered by rough paint. The experiments were conducted using a copper ring with a 1-mm diameter fully coated by rough paint with an average thickness of 2.3 μm. The resulting PA images exhibited up to 72% consistency despite the rough paint; the shapes of the objects were clearly recognized before and after coating. To conduct the experiment, simulations and image acquisitions were arranged. Then, the system capability to produce tomographic images was improved by adjusting the thermal diffusion lengths, and subsurface object images were successfully acquired at depths of 2.0, 2.6, 9.8, and 52 μm. The detailed composition of image slices displayed the structure profile of subsurface objects appropriately.

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Soil dielectric and senisitivity analysis for subsurface imaging applications based on distributed Sensor Networks

Dagefu

Sarabandi

2010

2010 IEEE International Geoscience and Remote Sensing Symposium

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High resolution subsurface imaging of deep targets based on distributed sensor networks

Cited by 5 publications

References 7 publications

Low Frequency Multi-Robot Networking

Low Frequency Multi-Robot Networking

Photoacoustic Tomography System for Roughly Painted Micro Objects

Soil dielectric and senisitivity analysis for subsurface imaging applications based on distributed Sensor Networks

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