Towards Turning Smartphones Into mmWave Scanners

Álvarez-Narciandi, Guillermo; Laviada, Jaime; Las-Heras, Fernando

doi:10.1109/access.2021.3067458

Cited by 24 publications

(30 citation statements)

References 31 publications

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“…is the near-field residual phase term due to the arbitrary scanning and MIMO effects in the near-field, as derived in (7). Hence, the virtual planar monostatic response can be efficiently acquired from the irregular samples by removing the residual phase to simultaneously account for the multi-planar scanning geometry and near-field multistatic effects.…”

Section: Signal Modelmentioning

confidence: 99%

“…To emulate irregular scanning geometries, the data collected throughout x-y-z space are subsampled, as discussed in Section V. Implementations in the literature employ multi-camera infrared camera systems to track the radar as it is moved through space by the user [10], [11]. Other studies on irregular scanning geometries have explored freehand imaging using a stereo camera with an IMU for positioning estimation [7] and UAV near-field imaging with a laser rangefinder and a real-time kinematic (RTK) system for localization [26]. These implementations, among others [12], [13], [27], [28], demonstrate the viability of high-resolution sensors for precise positioning to enable novel imaging techniques using UWB mmWave radars.…”

Section: Multi-planar Multistatic Imaging Hardware Prototypementioning

confidence: 99%

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Efficient 3-D Near-Field MIMO-SAR Imaging for Irregular Scanning Geometries

Smith

Torlak²

2022

IEEE Access

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In this article, we introduce a novel algorithm for efficient near-field synthetic aperture radar (SAR) imaging for irregular scanning geometries. With the emergence of fifth-generation (5G) millimeterwave (mmWave) devices, near-field SAR imaging is no longer confined to laboratory environments. Recent advances in positioning technology have attracted significant interest for a diverse set of new applications in mmWave imaging. However, many use cases, such as automotive-mounted SAR imaging, unmanned aerial vehicle (UAV) imaging, and freehand imaging with smartphones, are constrained to irregular scanning geometries. Whereas traditional near-field SAR imaging systems and quick personnel security (QPS) scanners employ highly precise motion controllers to create ideal synthetic arrays, emerging applications, mentioned previously, inherently cannot achieve such ideal positioning. In addition, many Internet of Things (IoT) and 5G applications impose strict size and computational complexity limitations that must be considered for edge mmWave imaging technology. In this study, we propose a novel algorithm to leverage the advantages of non-cooperative SAR scanning patterns, small form-factor multiple-input multiple-output (MIMO) radars, and efficient monostatic planar image reconstruction algorithms. We propose a framework to mathematically decompose arbitrary and irregular sampling geometries and a joint solution to mitigate multistatic array imaging artifacts. The proposed algorithm is validated through simulations and an empirical study of arbitrary scanning scenarios. Our algorithm achieves high-resolution and high-efficiency near-field MIMO-SAR imaging, and is an elegant solution to computationally constrained irregularly sampled imaging problems. Keywords 5G • automotive SAR • drone mmWave imaging • freehand imaging • handheld scanner • irregular sampling • mmWave imaging • multistatic imaging • real-time imaging • synthetic aperture radar (SAR)

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Section: Signal Modelmentioning

confidence: 99%

Section: Multi-planar Multistatic Imaging Hardware Prototypementioning

confidence: 99%

Efficient 3-D Near-Field MIMO-SAR Imaging for Irregular Scanning Geometries

Smith

Torlak²

2022

IEEE Access

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“…On one hand, this prototype includes a frequency modulated continuous mmWave (FMCW) radar module. In particular, the radar-on-chip BGT60TR24B evaluation board manufactured by Infineon [25] [37] has been chosen as it provides a tiny radar with a reduced power consumption, as it was originally developed to be used in mobile phones for gesture detection [38]. On the other hand, the LPMS-CURS2 IMU by LP-Research is used [39], as it comprises a compact board with USB interfacing.…”

Section: System Descriptionmentioning

confidence: 99%

“…However, most of these systems are just suitable for either indoor or outdoor environments and the majority of them involve the deployment of other sensors in the tracking environment. In addition, specialized devices, devoted to tracking, are slowly becoming available, allowing compact and reliable tracking with enough accuracy to enable mmWave SAR [25].…”

Section: Introductionmentioning

confidence: 99%

“…The position information is extracted using improved pedestrian dead reckoning techniques, fast sampling rates and new correction algorithms. Although other alternatives to extract the position information are feasible and they enable direct access to this location data [25] [36], the authors have used an IMU, as it is widely available and enables great compactness, but it should be noticed that the goal of this paper is not to introduce a new method for improving the existing algorithms to extract the position information from an IMU. The remainder of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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System Based on Compact mmWave Radar and Natural Body Movement for Assisting Visually Impaired People

et al. 2021

Self Cite

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The aim of this paper is to show how compact mmWave radar systems, attached to a person, can take advantage of their movements, in order to significantly improve the image resolution by means of synthetic aperture radar (SAR) techniques. Thus, high resolution imaging becomes possible even with tiny on-chip systems, opening up a horizon of possibilities to assist visually impaired people. The approach is illustrated for movements in terms of arm swings. For this purpose, it is firstly shown that the information from an inertial measurement unit (IMU) can be used to provide a trajectory estimation, which is enough to apply synthetic aperture radar processing. As a consequence, the resolution of the radar is greatly improved when compared with that achieved considering a single position. In order to avoid the continuously growing position error, commonly observed in dead-reckoning systems relying just on IMU, zero velocity updates (ZUPT) will be systematically applied. For doing so, two different zero velocity detectors (ZVD) are considered, one based on acceleration data and other on velocity estimation. Although the positioning information is extracted from the IMU, demonstrating the enhanced obstacle detection capabilities obtained with this approach, other sensors that can be carried by a person and that are capable of providing trajectory estimations to combine measurements acquired with compact mmWave radars could have been used. The system is tested using different targets and a good performance comparable to the one achieved by using a high accuracy reference positioning system is attained. The compactness of the system enables the possibility of using it as a wearable device, e.g., attached to the wrist. This shows that an IMU is enough for tracking relatively simple movements, though more complex positioning systems can be used for more general actions.INDEX TERMS Freehand imaging, visually impaired, inertial measurement unit, mmWave radar, synthetic aperture radar (SAR), wrist mounted imager, zero velocity detectors (ZVD).

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