Showing papers on "High dynamic range published in 2017"

Real-time Visual-Inertial Odometry for Event Cameras using Keyframe-based Nonlinear Optimization

Abstract: Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. We propose a novel, accurate tightly-coupled visual-inertial odom- etry pipeline for such cameras that leverages their outstanding properties to estimate the camera ego-motion in challenging conditions, such as high-speed motion or high dynamic range scenes. The method tracks a set of features (extracted on the image plane) through time. To achieve that, we consider events in overlapping spatio-temporal windows and align them using the current camera motion and scene structure, yielding motion-compensated event frames. We then combine these feature tracks in a keyframe- based, visual-inertial odometry algorithm based on nonlinear optimization to estimate the camera’s 6-DOF pose, velocity, and IMU biases. The proposed method is evaluated quantitatively on the public Event Camera Dataset [19] and significantly outperforms the state-of-the-art [28], while being computationally much more efficient: our pipeline can run much faster than real-time on a laptop and even on a smartphone processor. Fur- thermore, we demonstrate qualitatively the accuracy and robustness of our pipeline on a large-scale dataset, and an extremely high-speed dataset recorded by spinning an event camera on a leash at 850 deg/s.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

Abstract: The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Learning High Dynamic Range from Outdoor Panoramas

Abstract: Outdoor lighting has extremely high dynamic range. This makes the process of capturing outdoor environment maps notoriously challenging since special equipment must be used. In this work, we propose an alternative approach. We first capture lighting with a regular, LDR omnidirectional camera, and aim to recover the HDR after the fact via a novel, learning-based inverse tonemapping method. We propose a deep autoencoder framework which regresses linear, high dynamic range data from non-linear, saturated, low dynamic range panoramas. We validate our method through a wide set of experiments on synthetic data, as well as on a novel dataset of real photographs with ground truth. Our approach finds applications in a variety of settings, ranging from outdoor light capture to image matching.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging

Abstract: The ability to monitor respiratory rate is extremely important for medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake every day activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges. This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate in high dynamic range scenes.

A Fiber-Optic Fabry-Perot Accelerometer Based on High-Speed White Light Interferometry Demodulation

Abstract: A fiber-optic Fabry-Perot (F-P) accelerometer with high resolution, high dynamic range, high speed, and absolute measurement capability was developed and demonstrated in elevator health monitoring. The sensor element is based on a mesh diaphragm mass-loaded compact structure, and the F-P cavity interrogation was achieved by utilizing a high-speed white light interferometry demodulation algorithm. The displacement of inertial mass representing the change of F-P cavity was measured and translated to acceleration in real time. The results indicate a resonance frequency of 270 Hz and axial sensitivity of 3.86 μm/g within the frequency bandwidth of 10-120 Hz for the sensor. In experimental tests, the acceleration resolution achieved 8.5 μg within a ± 30 g maximum measurement range. The performance of the sensing system was compared with a commercialized piezoelectric accelerometer in monitoring the acceleration of an elevator.

Perceptually uniform color space for image signals including high dynamic range and wide gamut.

Abstract: A perceptually uniform color space has been long desired for a wide range of imaging applications. Such a color space should be able to represent a color pixel in three unique and independent attributes (lightness, chroma, and hue). Such a space would be perceptually uniform over a wide gamut, linear in iso-hue directions, and can predict both small and large color differences as well as lightness in high dynamic range environments. It would also have minimum computational cost for real time or quasi-real time processing. Presently available color spaces are not able to achieve these goals satisfactorily and comprehensively. In this study, a uniform color space is proposed and its performance in predicting a wide range of experimental data is presented in comparison with the other state of the art color spaces.

Pixel-by-pixel local dimming for high-dynamic-range liquid crystal displays

Abstract: We propose a high dynamic range (HDR) liquid crystal display (LCD) with pixel-level local dimming. The device structure consists of a pixelated LCD dimming panel to control the backlight intensity entering the master LCD panel. According to our analysis and test cell experiment, this dual-panel display system possesses exceedingly high contrast ratio (> 1,000,000:1) and high bit-depth (> 14 bits) at merely 5 volts. Meanwhile, to mitigate the Moire effect induced by the cascaded thin-film transistor (TFT) backplanes, we separate the two LCD panels with a polarization-dependent scattering film. The pros and cons of this HDR display are discussed.

Probing ultra-fast processes with high dynamic range at 4th-generation light sources: Arrival time and intensity binning at unprecedented repetition rates

Abstract: Understanding dynamics on ultrafast timescales enables unique and new insights into important processes in the materials and life sciences. In this respect, the fundamental pump-probe approach based on ultra-short photon pulses aims at the creation of stroboscopic movies. Performing such experiments at one of the many recently established accelerator-based 4th-generation light sources such as free-electron lasers or superradiant THz sources allows an enormous widening of the accessible parameter space for the excitation and/or probing light pulses. Compared to table-top devices, critical issues of this type of experiment are fluctuations of the timing between the accelerator and external laser systems and intensity instabilities of the accelerator-based photon sources. Existing solutions have so far been only demonstrated at low repetition rates and/or achieved a limited dynamic range in comparison to table-top experiments, while the 4th generation of accelerator-based light sources is based on superconducting radio-frequency technology, which enables operation at MHz or even GHz repetition rates. In this article, we present the successful demonstration of ultra-fast accelerator-laser pump-probe experiments performed at an unprecedentedly high repetition rate in the few-hundred-kHz regime and with a currently achievable optimal time resolution of 13 fs (rms). Our scheme, based on the pulse-resolved detection of multiple beam parameters relevant for the experiment, allows us to achieve an excellent sensitivity in real-world ultra-fast experiments, as demonstrated for the example of THz-field-driven coherent spin precession.

Progress Toward Accurate Measurement of Dielectric Barrier Discharge Plasma Actuator Power.

Abstract: The accurate measurement of power consumption by dielectric barrier discharge plasma actuators is a challenge due to the characteristics of the actuator current signal Microdischarges generate high-amplitude, high-frequency current spike transients superimposed on a low-amplitude, low-frequency current A high-speed digital oscilloscope was used to measure the actuator power consumption using the shunt resistor method and the monitor capacitor method The measurements were performed simultaneously and compared to each other in a time-accurate manner It was found that low signal-to-noise ratios of the oscilloscopes used, in combination with the high dynamic range of the current spikes, make the shunt resistor method inaccurate An innovative, nonlinear signal compression circuit was applied to the actuator current signal and yielded excellent agreement between the two methods The paper describes the issues and challenges associated with performing accurate power measurements It provides insights into the two methods including new insight into the Lissajous curve of the monitor capacitor method Extension to a broad range of parameters and further development of the compression hardware will be performed in future work

Review and Comparison of High-Dynamic Range Three-Dimensional Shape Measurement Techniques

Abstract: In the last decade, a significant number of techniques for three-dimensional (3D) shape measurement have been proposed. There are a large number of measurement demands for metallic workpieces with shiny surfaces in industrial applications; however, such shiny surfaces cannot be directly measured using the conventional structured light method. Therefore, various techniques have been investigated to solve this problem over the last few years. Some reviews summarize the different 3D imaging techniques; however, no comprehensive review exists that provides an insight into high-dynamic range (HDR) 3D shape measurement techniques used for shiny surfaces. We present a survey of recent HDR techniques for the digitization of shiny surfaces and classify and discuss the advantages and drawbacks of different techniques with respect to each other.

High-speed microstrip multi-anode multichannel plate detector system

Abstract: High-speed detector systems with high dynamic range and pulse width characteristics in the sub-nanosecond regime are mandatory for high resolution and highly sensitive time-of-flight mass spectrometers. Typically, for a reasonable detector area, an impedance-matched anode design is necessary to transmit the registered signal fast and distortion-free from the anode to the signal acquisition system. In this report, a high-speed microstrip multi-anode multichannel plate detector is presented and discussed. The anode consists of four separate active concentric anode segments allowing a simultaneous readout of signal with a dynamic range of about eight orders of magnitude. The impedance matched anode segments show pulse width of about 250 ps, measured at full width at half maximum, and rise time of ∼170 ps, measured with an oscilloscope with a sampling rate of 20 GS/s and 4 GHz analogue bandwidth. The usage of multichannel plates as signal amplifier allowed the design of a lightweight, low power consuming, and compact detector system, suitable, e.g., for the integration into space instrumentation or portable systems where size, weight, and power consumption are limited parameters.

Microchannel Plate Imaging Detectors for High Dynamic Range Applications

Abstract: Microchannel plate (MCP) imaging detectors are widely used in astronomical, biological imaging and remote sensing applications. Photon counting mode imagers with event timing can make use of the high spatial resolution (~10- $50~\mu \text {m}$ ) and very high time resolution (subnanoseconds) of MCP detectors to enhance the performance of such detectors in dynamic environments (for example airborne surveillance of moving objects, LIDAR, and 3-D topographic imaging). The total information that can be collected is limited by the dynamic range of the detector (cross delay line sensors can support detected photon rates up to ~2 MHz over the entire effective area). The ideal sensor for many applications, such as bright images or fast transient behavior, would combine the desirable attributes of high spatial and time resolution for each detected photon with event rates of 100 MHz or more. A new class of MCPs constructed using atomic layer deposition (ALD) on borosilicate glass microcapillary arrays is providing enhancements towards this goal. The ALD MCP manufacturing process decouples the operational functionalization from the substrate fabrication, opening the door for new resistive layers and high secondary emissive materials. Many improvements over traditional MCPs have been demonstrated, including robust substrates able to withstand high processing temperatures, very low background rates, high stable gains, and low outgassing. Higher global photon counting rates can be supported by ALD MCP detector schemes while greatly improving the instrument lifetime. Additionally, the robustness of these MCPs provide them with surface properties capable of supporting the deposition of a wide range of efficient photocathode materials (III-V), which require high processing temperatures (>500 C), to achieve a high quantum efficiency at near UV to near IR wavelengths. Sealed tube sensors incorporating nano-engineered MCPs can support nonproliferation and remote sensing enabling technologies by advancing the state-of the-art single-photon electro-optical remote sensing detectors. The progress of this effort, including results from the deposition of opaque photocathodes directly onto the front surface of the MCPs and the performance and lifetime characteristics of open faced and seal tube detectors, is reported here.

Computational Imaging on the Electric Grid

Abstract: Night beats with alternating current (AC) illumination. By passively sensing this beat, we reveal new scene information which includes: the type of bulbs in the scene, the phases of the electric grid up to city scale, and the light transport matrix. This information yields unmixing of reflections and semi-reflections, nocturnal high dynamic range, and scene rendering with bulbs not observed during acquisition. The latter is facilitated by a database of bulb response functions for a range of sources, which we collected and provide. To do all this, we built a novel coded-exposure high-dynamic-range imaging technique, specifically designed to operate on the grids AC lighting.

High Dynamic Range Imaging Technology [Lecture Notes]

Abstract: In this lecture note, we describe high dynamic range (HDR) imaging systems. Such systems are able to represent luminances of much larger brightness and, typically, a larger range of colors than conventional standard dynamic range (SDR) imaging systems. The larger luminance range greatly improves the overall quality of visual content, making it appear much more realistic and appealing to observers. HDR is one of the key technologies in the future imaging pipeline, which will change the way the digital visual content is represented and manipulated today.

Block-matching optical flow for dynamic vision sensors: Algorithm and FPGA implementation

Abstract: Rapid and low power computation of optical flow (OF) is potentially useful in robotics. The dynamic vision sensor (DVS) event camera produces quick and sparse output, and has high dynamic range, but conventional OF algorithms are frame-based and cannot be directly used with event-based cameras. Previous DVS OF methods do not work well with dense textured input and are designed for implementation in logic circuits. This paper proposes a new block-matching based DVS OF algorithm which is inspired by motion estimation methods used for MPEG video compression. The algorithm was implemented both in software and on FPGA. For each event, it computes the motion direction as one of 9 directions. The speed of the motion is set by the sample interval. Results show that the Average Angular Error can be improved by 30% compared with previous methods. The OF can be calculated on FPGA with 50 MHz clock in 0.2 us per event (11 clock cycles), 20 times faster than a Java software implementation running on a desktop PC. Sample data is shown that the method works on scenes dominated by edges, sparse features, and dense texture.

Hybrid, Frame and Event based Visual Inertial Odometry for Robust, Autonomous Navigation of Quadrotors

Abstract: Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide reliable visual information during high speed motions or in scenes characterized by high dynamic range. However, event cameras output only little information when the amount of motion is limited, such as in the case of almost still motion. Conversely, standard cameras provide instant and rich information about the environment most of the time (in low-speed and good lighting scenarios), but they fail severely in case of fast motions, or difficult lighting such as high dynamic range or low light scenes. In this paper, we present the first state estimation pipeline that leverages the complementary advantages of these two sensors by fusing in a tightly-coupled manner events, standard frames, and inertial measurements. We show on the publicly available Event Camera Dataset that our hybrid pipeline leads to an accuracy improvement of 130% over event-only pipelines, and 85% over standard-frames-only visual-inertial systems, while still being computationally tractable. Furthermore, we use our pipeline to demonstrate - to the best of our knowledge - the first autonomous quadrotor flight using an event camera for state estimation, unlocking flight scenarios that were not reachable with traditional visual-inertial odometry, such as low-light environments and high-dynamic range scenes.

Real-time FPGA-based Kalman filter for constant and non-constant velocity periodic error correction

Abstract: Displacement measuring interferometry has high resolution and high dynamic range, which is widely used in displacement metrology and sensor calibration. Due to beam leakage in the interferometer, imperfect polarization components, and ghost reflections, the displacement measurement suffers from periodic error, whose pitch is multiple harmonics of the Doppler frequency. In dynamic measurements, periodic error is usually on the order of nanometers, which impacts the dynamic measurement accuracy. This paper presents an approach to estimate and correct periodic error in real time based on an extended Kalman filter, which has the capability to deal with both constant and non-constant velocity motions. This algorithm is implemented on an application-specific hardware architecture in an FPGA, which has advantages in throughput and resource usage compared with conventional implementations. The measurement validation shows that this approach can effectively eliminate the periodic error for both constant and non-constant velocity motion, and the residual error reaches to the level of the background noise of the interferometer.

Blind high dynamic range image quality assessment using deep learning

Abstract: In this paper we propose a No-Reference Image Quality Assessment (NR-IQA) method on High Dynamic Range (HDR) images by combining deep Convolutional Neural Networks (CNNs) with saliency maps. The proposed method utilises the power of deep CNN architectures to extract quality features which can be applied cross HDR and Standard Dynamic Range (SDR) domains. To introduce human visual system to CNNs, a saliency map algorithm is used to select a subset of salient image patches to evaluate on. Our CNN-based method delivers a state-of-the-art performance in HDR NR-IQA experiment, competitive with full reference IQA methods.

Single-shot high dynamic range imaging via deep convolutional neural network

Abstract: We propose a single-shot high dynamic range (HDR) imaging algorithm with row-wise varying exposures in a single image using a deep convolutional neural network (CNN) We first convert an input raw Bayer image into irradiance values by calibrating rows with different exposures Then, we develop a new CNN model to restore missing information resulting from under- or over-exposed pixels and reconstruct the raw radiance map Finally, we obtain the HDR image by applying a demosaicing algorithm to the raw radiance map Experimental results on simulated images demonstrate that the proposed algorithm provides higher quality HDR images, with more details and less artifacts, than conventional algorithms

High dynamic range ultrasound imaging with real-time Filtered-Delay Multiply and sum beamforming

Abstract: Most commercially available ultrasound imaging systems currently implement the delay and sum (DAS) beamforming. Alternative beamformers have been presented, offering higher performance at the expense of computational complexity, which has so far limited their practical real-time implementation. In particular, the Filtered-Delay Multiply and Sum (F-DMAS) beamformer, which adds the computation of signed square roots, absolute values and multiplications to DAS, was recently shown to be effective in improving resolution, dynamic range and overall image quality. In this work, we present the real-time implementation of the F-DMAS beamformer on the ULA-OP 256 research system. This is obtained through a reformulation of the F-DMAS algorithm that allows reducing its computational cost. Compared to DAS, F-DMAS images of a commercial phantom captured in real-time showed higher CR (up to +7 dB), better spatial resolution (up to 30%), but lower CNR (−40%).

Design and Self-Noise of MET Closed-Loop Seismic Accelerometers

Abstract: Molecular electronic transfer (MET) technology offers an alternative approach for the development of accelerometers with high dynamic range and low self-noise. The best performance is achieved by using a force-balancing feedback. However, the operating principles of the feedback sensors has not been reporting yet, also, there is not any comprehensive theoretical model describing sensor noise in the complete operating frequency range. This paper reports on the development of the feedback system for an MET seismic accelerometer, a feedback stability analysis, and an optimization of the signal conditioning feedback electronics to get the highest dynamic range. Also, both the theoretical model and experimental results of such sensors self-noise are presented in the range of 0.1–120 Hz. According to the model and the experimental observation, there are two major contributors into self-noise: convective processes in the electrolyte and electronic noise of the signal operational amplifiers. The research results give better understanding of the molecular electronic accelerometers noise nature and suggest ways to reduce it.

High Dynamic Range X-Ray Detector Pixel Architectures Utilizing Charge Removal

Abstract: Several charge integrating CMOS pixel front ends utilizing charge removal techniques have been fabricated to extend dynamic range for X-ray diffraction applications at synchrotron sources and X-ray free electron lasers (XFELs). The pixels described herein build on the mixed mode pixel array detector (MM-PAD) framework, developed previously by our group to perform high dynamic range imaging. These new pixels boast several orders of magnitude improvement in maximum flux over the MM-PAD, which is capable of measuring a sustained flux in excess of $10{^{8}}$ X-rays/pixel/s while maintaining sensitivity to smaller signals, down to single X-rays. To extend dynamic range, charge is removed from the integration node of the front-end amplifier without interrupting integration. The number of times this process occurs is recorded by a digital counter in the pixel. The parameter limiting full well is, thereby, shifted from the size of an integration capacitor to the depth of a digital counter. The result is similar to that achieved by counting pixel array detectors, but the integrators presented here are designed to tolerate a sustained flux $>10{^{11}}$ X-rays/pixel/s. Pixel front-end linearity was evaluated by direct current injection and results are presented. A small-scale readout ASIC utilizing these pixel architectures has been fabricated and the use of these architectures to increase single X-ray pulse dynamic range at XFELs is discussed briefly.

High Precision Laser Scanning of Metallic Surfaces

Abstract: Speckle noise, dynamic range of light intensity, and spurious reflections are major challenges when laser scanners are used for 3D surface acquisition. In this work, a series of image processing operations, that is, Spatial Compound Imaging, High Dynamic Range Extension, Gray Level Transformation, and Most Similar Nearest Neighbor are proposed to overcome the challenges coming from the target surface. A prototype scanner for metallic surfaces is designed to explore combinations of these image processing operations. The main goal is to find the combination of operations that will lead to the highest possible robustness and measurement precision at the lowest possible computational load. Inspection of metallic tools where the surface of its edge must be measured at micrometer precision is our test case. Precision of heights measured without using the proposed image processing is firstly analyzed to be ±7.6 μm at 68% confidence level. The best achieved height precision was ±4.2 μm. This improvement comes at 24 times longer processing time and five times longer scanning time. Dynamic range extension of the image capture improves robustness since the numbers of saturated or underexposed pixels are substantially reduced. Using a high dynamic range (HDR) camera offers a compromise between processing time, robustness, and precision.

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging

Abstract: In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

Collaboratively Adaptive Vibration Sensing System for High-fidelity Monitoring of Structural Responses Induced by Pedestrians

Abstract: This paper presents a collaboratively adaptive vibration monitoring system that captures high fidelity structural vibration signals induced by pedestrians. These signals can be used for various human activity monitoring by inferring information about the impact sources, such as pedestrian footsteps, door open closing, dragging objects. Such applications often require high fidelity (high resolution and low distortion) signals. Traditionally, expensive high resolution and high dynamic range sensors are adopted to ensure sufficient resolution. However, for sensing systems that use low-cost sensing devices, the resolution and dynamic range are often limited; hence this type of sensing methods is not well explored ubiquitously. We propose a low-cost sensing system that utilizes 1) a heuristic model of the investigating excitations and 2) shared information through networked devices to adapt hardware configurations and obtain high fidelity structural vibration signals. To further explain the system, we use indoor pedestrian footstep sensing through ambient structural vibration as an example to demonstrate the system performance. We evaluate the application with three metrics that measure the signal quality from different aspects: the sufficient resolution rate to present signal resolution improvement without clipping, the clipping rate to measure the distortion of the footstep signal, and the signal magnitude to quantify the detailed resolution of the detected footstep signal. In experiments conducted in a school building, our system demonstrated up to 2X increase in the sufficient resolution rate and 2X less error rate when used to locate the pedestrians as they walk along the hallway, compared to a fixed sensing setting.

High resolution, wide field of view, real time 340GHz 3D imaging radar for security screening

Abstract: The EU FP7 project CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) is developing a demonstrator system for next generation airport security screening which will combine passive and active submillimeter wave imaging sensors. We report on the development of the 340 GHz 3D imaging radar which achieves high volumetric resolution over a wide field of view with high dynamic range and a high frame rate. A sparse array of 16 radar transceivers is coupled with high speed mechanical beam scanning to achieve a field of view of ~ 1 x 1 x 1 m3 and a 10 Hz frame rate.