We present a portable 3-D millimeter wave imaging system operating in the K-band (24 GHz). This imaging system consists of a multiple input, multiple output (MIMO) array of 32 transmit elements and 32 receive elements that illuminates a scene with millimeter wave energy and processes the reflected signals to reconstruct a 3-D image. To achieve an acceptable image resolution from this sparse array, the system combines multiple measurements while the sensor is moved relative to the scene being imaged. For ease of portability, the imaging system uses a single Ethernet cable to power the sensor and transfer the captured raw data to a laptop computer. A graphics processing unit (GPU)-optimized image reconstruction algorithm transforms the raw data to a 3-D image with approximately 1 cm voxel resolution, which is rendered in 3-D in a Web browser based user interface. We present measured test images and demonstrate an achieved dimensioning accuracy of ±1 − 3 mm when the system is used to detect and dimension objects hidden behind opaque building materials such as drywall, plywood, ceramic tile, vinyl flooring, and cement.

Lens-less millimeter-wave (mmWave) imaging of moving objects using a sparse array relies on knowledge of the relative positions between the moving object and the imaging system to enable coherent image reconstruction. However, accurate object position information is rarely available in commercial applications where the moving object, e.g. a conveyor belt or a robot, is controlled independently of the imaging system, or where the imaged objects move autonomously. This poses a significant hurdle for many commercial mmWave imaging applications. We present a video-based motion extraction approach for active mmWave imaging. The object velocity is extracted in real time from motion vectors obtained from a compressed video. This information is combined with readouts from a distance sensor to infer the position of the object at each time instant. Leveraging video-derived motion vectors enables the offloading of computational complexity of 2-D spatial correlations to highly optimized algorithms operating on camera frames. We show experimentally that the image quality of a commercial high-throughput 3-D mmWave imaging system prototype is improved significantly by this approach when the velocity of the target is unknown and time-varying. We furthermore show that image quality is also improved compared to known average motion profiles of the imaged objects. Using a lab setup with known ground truth, we show that the RMS position error is 2.5 mm over a travel length of 0.52 m. This is better than 1/8 of the wavelength at K-band (24 GHz) along the trajectory and thus sufficient to achieve excellent image quality at K-band and longer wavelengths.

This paper presents an extension of synthetic aperture radar (SAR) techniques to enable simultaneous radar imaging, sensor tag localization, and backscatter-based data uplink from multiple sensor tags in a cluttered environment. A unified system model is presented that leverages coherent processing of backscattered signals gathered over the synthetic aperture for all three of these purposes. The proposed approach, using balanced orthogonal codes for SAR-based localization as well as the backscatter data uplink, is shown to have several favorable properties, including straightforward tag-vs-clutter discrimination, straightforward multiple access among tags, and improved signal-to-noise ratio during localization. A proof-of-principle indoor experiment is presented in the X-band (10-13 GHz) using two custom-designed backscatter tags interrogated by a vector network analyzer functioning as an FMCW radar. The proposed system model is validated by simultaneous imaging of a cluttered scene, tag localization with a maximum range error of 9 mm, and data demodulation from both tags telemetering temperature changes at a rate of 1 bit/s at ranges of 4.4 m and 4.7 m. The resulting point-spread functions of tags demonstrate a range resolution of 4.7 cm and a cross-range resolution of 9.1 cm.

Emerging metasurface antenna technology enables flexible and low cost massive multiple-input multiple-output (MIMO) millimeter-wave (mm W) imaging for applications such as personnel screening, weapon detection, reconnaissance, and remote sensing. This work proposes an orthogonal coded active illumination (OCAI) approach which utilizes simultaneous, mutually orthogonal coded transmit signals to illuminate the scene being imaged. It is shown that OCAI is robust to code amplitude and code phase imbalance introduced by imperfect transmitter (TX) and receiver (RX) hardware, while also mitigating common impairments of low cost direct-conversion receivers, such as RX self-jamming and DC offsets. The coding gain offered by this approach improves imager signal to noise ratio performance by up to 15 dB using codes of symbol length 32. We present validation images of resolution targets and a human-scale mannequin, obtained with a custom massive-MIMO mm W imager having 24 simultaneous TXs and 72 simultaneous RXs operating in the K-band (17.5 GHz to 26.5 GHz). The imager leverages both spatial coding via frequency diverse metasurface antennas, and temporal coding via OCAI of the scene.

We present a 5.8 GHz Fresnel-zone microwave wireless power transfer experiment leveraging a large planar holographic metasurface reflectarray to form a focused spot at a distance of 6.5 m. The 1.5 m 2 holographic metasurface is fabricated from 15 panels having total dimensions of 122×127 cm, and is comprised of over 4,000 reflective patch resonators on the top surface of a 3.0 mm thick FR-4 substrate. A constrained hologram approach is used to discretize the desired hologram and approximate the desired focal spot given the Lorentzian coupled amplitude-phase response of the patch resonators. When the metasurface is illuminated by a 20 dB standard-gain horn 1.8 m away, it produces a spot with a 3 dB beam waist (FWHM) of approximately 50 cm. The experimentally measured beam profile matches the simulated beam profile to ± 1 dB within the beam, and we estimate almost 40% of the transmitted power was incident onto the receiver at the focus point.

We demonstrate a low-profile holographic imaging system at millimeter wavelengths based on an aperture composed of frequency-diverse metasurfaces. Utilizing measurements of spatially-diverse field patterns, diffraction-limited images of human-sized subjects are reconstructed. The system is driven by a single microwave source swept over a band of frequencies (17.5–26.5 GHz) and switched between a collection of transmit and receive metasurface panels. High fidelity image reconstruction requires a precise model for each field pattern generated by the aperture, as well as the manner in which the field scatters from objects in the scene. This constraint makes scaling of computational imaging systems inherently challenging for electrically large, coherent apertures. To meet the demanding requirements, we introduce computational methods and calibration approaches that enable rapid and accurate imaging performance.

Undesired local oscillator (LO) leakage and dc offset impairments are commonly observed when direct conversion (or homodyne) receivers (RXs) are used for coherent millimeter-wave (mmW) active imaging, and are particularly severe when imaging short-range, slow-moving targets where the target’s baseband response is close to dc. This letter proposes a binary phase shift keying (BPSK) coding scheme, which modulates the illumination source to mitigate dc offset and self-jamming in the receiver I/Q demodulator. This modulation permits the separation of the desired point-scatterer returns that form the mmW image from the undesired components. In a proof of principle experiment using a $K$ -band (17.5–26.5-GHz) short-range mmW imaging setup, the suppression of dc offset and LO leakage using a BPSK-modulated source is demonstrated. It is shown that the dc offset has been reduced by over $400\times $ and the receiver sensitivity has improved by over 40 dB. The proposed direct conversion approach with coded illumination holds promise for reducing the cost and complexity of mmW imaging systems versus conventional superheterodyne mmW imaging systems.

We present a modulated ultrawideband backscatter calibration target (fiducial) intended for group delay calibration in large-aperture multitransceiver millimeter-wave imagers. The fiducial is designed to resemble a modulated point scatterer across the K-band (17.5–26.5 GHz). Multiple such fiducials may be used to mitigate thermal and mechanical drift across multiple transceivers comprising the imager. This approach allows tracking and removing both time-varying amplitude and phase drift in the RF hardware and associated cables. Backscatter modulation of the fiducial allows the system to separate the fiducial from the imaged scene and clutter in the environment. We show that the −10 dB beamwidth of the proposed fiducial is approximately 84° along the azimuth plane and 60° along the elevation plane. A proof of concept group delay calibration experiment is presented for a K-band laboratory setup, where a single fiducial and a metal plate target are placed in a scene together. After the backscatter-based calibration, the measured range error of the metal plate at a two-way slant distance of 70.54 cm is reduced to only 1.06 mm (0.15% position error).

We present a localization and multiple access method for backscatter sensor networks based on synthetic aperture radar (SAR) techniques. Two sensor tags, each consisting of a wideband bow-tie antenna, a PIN switch, and an Arduino Nano, were designed for an indoor measurement over the 10–13 GHz band. With a synthetic aperture size of 0.6 m, the sensor tags can be imaged separately or in combination at ranges up to 4 m. A cross-range resolution of 8 cm and a range resolution of 4.6 cm were achieved at a range of 4 m, with errors of less than 4 cm.

We present a low cost X-band microwave backscatter communication testbed incorporating integrated planar wideband bow-tie antennas. This testbed leverages low cost silicon germanium (SiGe) integrated circuits intended for the satellite television market to provide an experimental capability for backscatter experimentation in the 10.0 GHz to 11.1 GHz band. The integrated wideband bow-tie antennas have a 10 dB return loss bandwidth of 9.63-13.15 GHz and a gain of 6 dBi. The transmitter consists of a single-chip frequency synthesizer and buffer amplifier with an output power of -2 dBm. The receive downconverter consists of an integrated LNA, mixer, and LO frequency synthesizer, with an RF frequency range of 10.0 GHz to 13.0 GHz and an IF frequency range of 250 MHz to 3250 MHz. The downconverter's measured conversion gain is 36 dB with a noise figure of 7 dB. The IF signal processing leverages a Universal Software Radio Peripheral (USRP) to support arbitrary backscatter modulation schemes such as ASK, PSK, or QAM backscatter with an IF bandwidth up to 50 MHz. We found good agreement between the measured and simulated free-space path loss at ranges of up to 4.1 m in a laboratory environment, and demonstrate the use of this testbed in a BPSK backscatter configuration at a rate of 10 Mbps.

Since the time of Nikola Tesla, the dream of ubiquitous wireless power transfer (WPT) has tantalized generations of inventors and engineers. A practical, ubiquitous WPT infrastructure could offer tremendous benefits for mobile devices, such as extending battery lifetime, on-the-fly recharging, or, in some cases, eliminating batteries and pesky charging cords altogether. But these benefits can be achieved only if the spatial and temporal distribution of wireless power can be controlled. The authors consider approaches to achieving control over the distribution of long-range (electromagnetic far-field) wireless power, using multi-input, multi-output (MIMO) concepts adapted from the communication domain. They survey recent results in MIMO WPT theory and experiment, and conclude with their own experimental evidence that MIMO WPT can leverage the physics of multipath propagation to selectively enhance or block wireless power delivery, with a typical control range of 20 dB (100 times) in practical indoor environments. This article is part of a special issue on energy harvesting.

We present a method for enhancing far-field wireless power transfer (WPT) to nonlinear, passive UHF RFID backscatter transponders using a multi-input multi-output (MIMO) base station. The proposed method does not require on-tag power measurements or on-tag channel estimation, either of which would add significant complexity and power consumption for microwatt-class wirelessly powered devices such as passive UHF RFID tags. We show in a measurement-based proof of concept that WPT optimization to nonlinear backscatter transponders is possible solely based on the backscatter signal, without knowledge of the incident power level at the tag or prior knowledge of the tag's characteristics. Using an 8×8 MIMO transceiver array to optimize power delivery, we observed an average WPT enhancement of 8.9 dB relative to an un-optimized 8-transmitter configuration across a 50m3 volume in an office/lab environment. We also show that power to a given tag can be selectively denied, with a notch depth of -106.4 dB (noise floor of the presented measurements). These results are comparable to values previously observed for linear backscatter transponders, and suggest that the use of MIMO interrogators could lead to improved forward-link performance and thus efficiently provide power for sensors or other new power-hungry functions on passive transponders.

High-accuracy localization remains a much desired but elusive feature for passive radio transponders as used in radio-frequency identification (RFID). We believe that the principle of cognitive radar can overcome the fundamental physical limitations hindering its implementation. We propose to jointly employ a narrowband radio to interrogate the transponders and an adaptive (ultra) wideband backscatter radio for the target tracking and for actuating, sensing, and learning the radio environment. This paper explores system model and key processing perception-action cycle steps of such a cognitive secondary radar. At its core is a perception-action cycle, which consists of transmitter and receiver-side environment models for representing radio channel conditions and Bayesian trackers for the target states. Multipath is exploited to improve the robustness and to make optimum use of the radar's sensing capabilities. Feedback information is derived from the Cramέr-Rao lower bound on the position error. Initial results are presented as a basic proof of principle.

We present an efficient method for enhancing far-field wireless power transfer (WPT) to highly power-constrained mobile devices such as UHF and microwave RFID transponders using a multiple-input-multiple-output (MIMO) base station system. Existing techniques for channel estimation are prohibitively complex and consume too much power to be integrated into milliwatt- or microwatt-class wirelessly powered devices. We show that power transfer can be optimized using a transponder's backscatter signal alone, without requiring channel estimation and power measurement circuitry on the transponder. A measurement-based proof of concept is presented, illustrating that for any linear backscatter transponder, power optimization based on the backscattered signal is equivalent to local measurement at the mobile device itself. Using an 8 × 8 MIMO transceiver array to optimize power delivery across 100 randomly chosen locations in our office environment, we observe an average WPT enhancement of 8.1 dB relative to an unoptimized transmitter configuration. Transponders with nonlinear power harvesters can easily be supported with the addition of a single RF switching transistor.

Sei es im Straßenverkehr oder in der Freizeit, zum Beispiel beim Wandern: Wir sind daran gewöhnt, überall verlässlich unsere Position bestimmen zu können. Sobald man aber ein Gebäude betritt, so ändert sich die Situation, vor allem, weil Satellitensignale nicht länger empfangen werden können. Die Liste der möglichen Anwendungsszenarien, die genaue Innenraum-Lokalisierung benötigen, ist jedoch lang: Großeinsätze von Rettungskräften, Verfolgung von Waren in der Logistik oder Leiten von Besuchern und Besucherinnen durch Museen sind nur ein Auszug davon.