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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.

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).

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 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 $\mathbf{m}^{2}$ holographic metasurface is fabricated from 15 panels having total dimensions of $\mathbf{122}\times \mathbf{127}$ 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 $\mathbf{m}$ 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.

Computational imaging is a proven strategy for obtaining high-quality images with fast acquisition rates and simpler hardware. Metasurfaces provide exquisite control over electromagnetic fields, enabling the radiated field to be molded into unique patterns. The fusion of these two concepts can bring about revolutionary advances in the design of imaging systems for security screening. In the context of computational imaging, each field pattern serves as a single measurement of a scene; imaging a scene can then be interpreted as estimating the reflectivity distribution of a target from a set of measurements. As with any computational imaging system, the key challenge is to arrive at a minimal set of measurements from which a diffraction-limited image can be resolved. Here, we show that the information content of a frequency-diverse metasurface aperture can be maximized by design, and used to construct a complete millimeter-wave imaging system spanning a 2 m by 2 m area, consisting of 96 metasurfaces, capable of producing diffraction-limited images of human-scale targets. The metasurfacebased frequency-diverse system presented in this work represents an inexpensive, but tremendously flexible alternative to traditional hardware paradigms, offering the possibility of low-cost, real-time, and ubiquitous screening platforms.

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.

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.

A comprehensive characterization and model of the UHF RFID channel is presented for narrowband through ultra-wideband tag localization systems. The analyses are based on ultra-wideband channel measurements in a warehouse portal, centered around 900 MHz. Measured scenarios include an electromagnetically transparent pallet and a pallet containing liquids, each for a portal shielded by metal backplanes and for a portal shielded by absorbing material. The presented analyses cover the individual channels to and from the tag, the feedback channel, and the backscatter channel, for bi- and monostatic reader setups. We find that the direct path is rarely dominant on the backscatter link despite clear line-of-sight conditions and directive reader antennas. The power ratio between the direct and all indirect paths ranges from -20 through 5 dB for the more common metal portal, and RMS delay spreads are in the range of 10-80 ns. Since only the direct (line-of-sight) path carries the correct distance/direction information, tag localization in such portals requires high robustness with respect to weak line-of-sight components. We also show that classical channel models in UHF RFID, despite predicting the incident power level at the tag accurately, produce far too optimistic estimates of channel parameters relevant to ranging and localization.

The wireless channel of backscatter radio systems is a two-way pinhole channel, created by the concatenation of two standard wireless channels. We present a method to calculate wideband channel parameters of backscatter channels based on the parameters of the constituent one-way channels. The focus is on characteristics that are vital for narrowband and wideband ranging, such as the K-factor w.r.t. the direct (line-of-sight) path and the RMS delay spread. The presented analyses include uncorrelated as well as correlated channel pairs and are thus valid for bistatic and monostatic antenna setups. We also show that the uncorrelated scattering (US) assumption holds for the backscatter channel provided that the constituent channels are US.

In this paper, we present the extension of a recently published two-frequency continuous-wave (CW) ultra-high-frequency RF identification ranging technique to multiple carriers. The proposed system concept relies on exact phase information; hence, the passive tag cannot be accurately modeled as a frequency-flat linear device. A linearized model of the tag's reflection coefficient is devised to bridge the gap between the nonlinear reality and the linear CW radar theory. Estimation error bounds are derived and effects caused by noise and multipath propagation are analyzed in detail. It has been found that systematic errors introduced by the tag's reflection characteristic cannot be compensated by using multiple carriers due to large variations caused by detuning. Nonetheless the system, while being vulnerable to multipath propagation effects, still performs well under line-of-sight conditions; mean average errors below 15% of the true distance are possible in typical fading environments..

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 Cramer-Rao lower bound on the position error. Initial results are presented as a basic proof of principle.

We present a detailed analysis of an indoor UWB channel measurement campaign. The focus is on the modeling of the deterministic part of the multipath channel using a-priori known relevant reflections and scatterers, found from an available floor plan. Our approach uses virtual signal sources, whose locations and visibilities can be calculated using simple ray-launching techniques. The channel analysis steps exploit these results, using an effective multipath cancellation method that introduces virtually no artifacts. We show that the corresponding multipath-components can explain up to 90% of the UWB channel impulse responses in terms of energy capture. This is important for multipath-aided indoor localization, which provides robust position fixes using a single base station only.

In this paper the impact of the signal bandwidth on the performance of frequency modulated continuous wave (FMCW) radar based ranging to ultra high frequency (UHF) radio frequency identification (RFID) tags is investigated. The analyses are based on ultra-wideband (UWB) channel measurements performed in a warehouse portal, which is a severe multipath environment. It is illustrated that the available bandwidth of the usual ISM bands at 900 MHz, 2.5 GHz and 5.8 GHz is only sufficient for a precise RFID tag localization if moderate or low multipath conditions are given. However, in severe multipath channels the ISM bands are unsuited and UWB signals are needed. The results can be considered a lower bound for signal time of flight (TOF) based localization approaches that utilize Fourier or correlation methods for the signal travel time estimation.

A chip manufacturing process requires extensive support of CAD-tools in order to predict the behavior of the embedded circuitry and to ensure the intended system functionality. Past experience shows that the overall performance of UHF RFID systems is mainly limited by multipath propagation and detuning. In this context, system-level simulations are vital to assess the overall performance and improve the embedded circuit. We present a simulator framework capable of handling chip-level tag models, fading MIMO radio channels, and interrogator building blocks on signal level. It is based on highly flexible behavioral tag-models instead of highly accurate but static ASIC models. In contrast to other UHF RFID simulators, it is explicitly designed to handle wideband signals, fading channels, nonlinearities, and detuning effects. The simulator is currently used to develop and evaluate the performance of ranging and realtime channel estimation systems. The presented results emphasize the feasibility of our framework in the evaluation of a range estimation approach between a standard UHF RFID transponder and an interrogator.