60GHz Mobile Imaging Radar

Zhu, Yibo; Zhu, Yanzi; Zhang, Zengbin; Zhao, Ben Y.; Zheng, Haitao

doi:10.1145/2699343.2699363

Cited by 22 publications

(21 citation statements)

References 19 publications

(23 reference statements)

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“…Our initial work in this space explored the possibility of using device mobility to emulate a virtual antenna array with large aperture [52]. This design uses the mobile device as a receiver, with a decoupled transmitter either embedded in the infrastructure or "deployed" on-demand by the user, (e.g., mounted on a nearby drone).…”

Section: Rf Imaging Via 60ghz Networking Radiosmentioning

confidence: 99%

“…Using 60GHz beams is especially advantageous here. Since 60GHz has a carrier wavelength of 5mm (12x shorter than WiFi/cellular), a user using 60GHz links can obtain fine-grain resolution with just small movements in the measurement area [52].…”

Section: Rf Imaging Via 60ghz Networking Radiosmentioning

confidence: 99%

“…Our earlier work proposed a 60GHz imaging system [52], where the receiver estimates object location and surface boundary using the Synthetic Array Radar (SAR) algorithm [14]. Applying SAR on measurements along a trajectory emulates the process where a large array focuses its narrow beam on different points of the object surface.…”

Section: A Synthetic Array Radar (Sar) Systemmentioning

confidence: 99%

“…Existing design [52] makes two "idealistic" assumptions on device positioning: (1) TX and RX have perfect knowledge of their relative position; (2) RX moves in a perfect trajectory e.g. a straight line.…”

Section: Limitations Of Sarmentioning

confidence: 99%

“…An alternative solution is to use "unfocused" SAR which assumes {φi} N i=1 are all identical, i.e. φi = 0, and only uses RSS to compute P(p) [52]. This reduces the impact of trajectory errors, but sacrifices imaging resolution: the longer the receiver trajectory, the more the "uniform phase approximation" error amplifies and degrades imaging accuracy.…”

Section: Limitations Of Sarmentioning

confidence: 99%

See 4 more Smart Citations

Reusing 60GHz Radios for Mobile Radar Imaging

Zhu

Zhao

et al. 2015

Proceedings of the 21st Annual International Conference on Mobile Computing and Networking

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110

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The future of mobile computing involves autonomous drones, robots and vehicles. To accurately sense their surroundings in a variety of scenarios, these mobile computers require a robust environmental mapping system. One attractive approach is to reuse millimeterwave communication hardware in these devices, e.g. 60GHz networking chipset, and capture signals reflected by the target surface. The devices can also move while collecting reflection signals, creating a large synthetic aperture radar (SAR) for high-precision RF imaging. Our experimental measurements, however, show that this approach provides poor precision in practice, as imaging results are highly sensitive to device positioning errors that translate into phase errors. We address this challenge by proposing a new 60GHz imaging algorithm, RSS Series Analysis, which images an object using only RSS measurements recorded along the device's trajectory. In addition to object location, our algorithm can discover a rich set of object surface properties at high precision, including object surface orientation, curvature, boundaries, and surface material. We tested our system on a variety of common household objects (between 5cm-30cm in width). Results show that it achieves high accuracy (cm level) in a variety of dimensions, and is highly robust against noises in device position and trajectory tracking. We believe that this is the first practical mobile imaging system (re)using 60GHz networking devices, and provides a basic primitive towards the construction of detailed environmental mapping systems.

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Section: Rf Imaging Via 60ghz Networking Radiosmentioning

confidence: 99%

Section: Rf Imaging Via 60ghz Networking Radiosmentioning

confidence: 99%

Section: A Synthetic Array Radar (Sar) Systemmentioning

confidence: 99%

Section: Limitations Of Sarmentioning

confidence: 99%

Section: Limitations Of Sarmentioning

confidence: 99%

See 3 more Smart Citations

Reusing 60GHz Radios for Mobile Radar Imaging

Zhu

Zhao

et al. 2015

Proceedings of the 21st Annual International Conference on Mobile Computing and Networking

Self Cite

110

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Ultrasound sounding in air by fast-moving receiver

Sukhanov

Erzakova

2018

IOP Conf. Ser.: Mater. Sci. Eng.

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Towards In-baggage Suspicious Object Detection Using Commodity WiFi

Wang

Liu

Chen

et al. 2018

2018 IEEE Conference on Communications and Network Security (CNS)

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The growing needs of public safety urgently require scalable and low-cost techniques on detecting dangerous objects (e.g., lethal weapons, homemade-bombs, explosive chemicals) hidden in baggage. Traditional baggage check involves either high manpower for manual examinations or expensive and specialized instruments, such as X-ray and CT. As such, many public places (i.e., museums and schools) that lack of strict security check are exposed to high risk. In this work, we propose to utilize the finegrained channel state information (CSI) from off-the-shelf WiFi to detect suspicious objects that are suspected to be dangerous (i.e., defined as any metal and liquid object) without penetrating into the user's privacy through physically opening the baggage. Our suspicious object detection system significantly reduces the deployment cost and is easy to set up in public venues. Towards this end, our system is realized by two major components: it first detects the existence of suspicious objects and identifies the dangerous material type based on the reconstructed CSI complex value (including both amplitude and phase information); it then determines the risk level of the object by examining the object's dimension (i.e., liquid volume and metal object's shape) based on the reconstructed CSI complex of the signals reflected by the object. Extensive experiments are conducted with 15 metal and liquid objects and 6 types of bags in a 6-month period. The results show that our system can detect over 95% suspicious objects in different types of bags and successfully identify 90% dangerous material types. In addition, our system can achieve the average errors of 16ml and 0.5cm when estimating the volume of liquid and shape (i.e., width and height) of metal objects, respectively.

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60GHz Mobile Imaging Radar

Cited by 22 publications

References 19 publications

Reusing 60GHz Radios for Mobile Radar Imaging

Reusing 60GHz Radios for Mobile Radar Imaging

Ultrasound sounding in air by fast-moving receiver

Towards In-baggage Suspicious Object Detection Using Commodity WiFi

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