Pyroelectric detector signal measurement and processing

Práce se zabývá fyzikálními vlastnostmi pyroelektrických senzorů a jejich praktickým využitím. Součástí práce je návrh a realizace měřící aparatury, jež bude využita k měření fyzikálních vlastností senzorů. Pro měření signálů pyroelektrického senzoru bude navržen nízkošumový zesilovač. Součástí práce je také návrh a realizace algoritmu pro lokalizaci infračerveného zdroje záření (plamene) v prostoru, na základě vyhodnoceného analogového signálu.The thesis analyzes the physical properties of the pyroelectric sensors and its practical use. Essential part of the work is the design and realization of the measuring set-up, which is used for the measurements of the sensors physical properties. With this workbench, main parameters of the pyroelectric sensors have been obtained. The second part of the work deals with a low noise preamplifier designing. This device was designed for the pyroelectric sensor signal measurements. The amplifier is designed to be used for a low noise, wide band measuring. During the process of amplifier designing, all the noise components have been investigated separately, using operational amplifiers models. The objective of the last part of this work is to develop the system, which would be able to localize an infrared (IR) emitting source located somewhere in the space between the installed pyroelectric sensors. For this purpose, classical localization methods could be used as well as the artificial neural networks (ANN), which are becoming still more popular these days. The system is able to detect the exact placement of the IR radiation source.

Continuous-wave frequency upconversion with a molecular optomechanical nanocavity

[EN] Coherent upconversion of terahertz and mid-infrared signals into visible light opens new horizons for spectroscopy, imaging, and sensing but represents a challenge for conventional nonlinear optics. Here, we used a plasmonic nanocavity hosting a few hundred molecules to demonstrate optomechanical transduction of submicrowatt continuous-wave signals from the mid-infrared (32 terahertz) onto the visible domain at ambient conditions. The incoming field resonantly drives a collective molecular vibration, which imprints a coherent modulation on a visible pump laser and results in upconverted Raman sidebands with subnatural linewidth. Our dual-band nanocavity offers an estimated 13 orders of magnitude enhancement in upconversion efficiency per molecule. Our results demonstrate that molecular cavity optomechanics is a flexible paradigm for frequency conversion leveraging tailorable molecular and plasmonic properties.This work received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement nos. 829067 (FET Open THOR), 820196 (ERC CoG QTONE), and 732894 (HOT). C.G. acknowledges support from the Swiss National Science Foundation (project nos. 170684 and 198898). This work is part of the research program of the Netherlands Organisation for Scientific Research (NWO). A.I.B. acknowledges financial support by the Alexander von Humboldt Foundation.Chen, W.; Roelli, P.; Hu, H.; Verlekar, S.; Amirtharaj, SP.; Barreda, ÁI.; Kippenberg, TJ.... (2021). Continuous-wave frequency upconversion with a molecular optomechanical nanocavity. Science. 374:1264-1267. https://doi.org/10.1126/science.abk31061264126737

Energy Efficiency in Communications and Networks

The topic of "Energy Efficiency in Communications and Networks" attracts growing attention due to economical and environmental reasons. The amount of power consumed by information and communication technologies (ICT) is rapidly increasing, as well as the energy bill of service providers. According to a number of studies, ICT alone is responsible for a percentage which varies from 2% to 10% of the world power consumption. Thus, driving rising cost and sustainability concerns about the energy footprint of the IT infrastructure. Energy-efficiency is an aspect that until recently was only considered for battery driven devices. Today we see energy-efficiency becoming a pervasive issue that will need to be considered in all technology areas from device technology to systems management. This book is seeking to provide a compilation of novel research contributions on hardware design, architectures, protocols and algorithms that will improve the energy efficiency of communication devices and networks and lead to a more energy proportional technology infrastructure

LISA Metrology System - Final Report

Gravitational Waves will open an entirely new window to the Universe, different from all other astronomy in that the gravitational waves will tell us about large-scale mass motions even in regions and at distances totally obscured to electromagnetic radiation. The most interesting sources are at low frequencies (mHz to Hz) inaccessible on ground due to seismic and other unavoidable disturbances. For these sources observation from space is the only option, and has been studied in detail for more than 20 years as the LISA concept. Consequently, The Gravitational Universe has been chosen as science theme for the L3 mission in ESA's Cosmic Vision program. The primary measurement in LISA and derived concepts is the observation of tiny (picometer) pathlength fluctuations between remote spacecraft using heterodyne laser interferometry. The interference of two laser beams, with MHz frequency difference, produces a MHz beat note that is converted to a photocurrent by a photodiode on the optical bench. The gravitational wave signal is encoded in the phase of this beat note. The next, and crucial, step is therefore to measure that phase with µcycle resolution in the presence of noise and other signals. This measurement is the purpose of the LISA metrology system and the subject of this report

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques

Nonlinear models and algorithms for RF systems digital calibration

Focusing on the receiving side of a communication system, the current trend in pushing the digital domain ever more closer to the antenna sets heavy constraints on the accuracy and linearity of the analog front-end and the conversion devices. Moreover, mixed-signal implementations of Systems-on-Chip using nanoscale CMOS processes result in an overall poorer analog performance and a reduced yield. To cope with the impairments of the low performance analog section in this "dirty RF" scenario, two solutions exist: designing more complex analog processing architectures or to identify the errors and correct them in the digital domain using DSP algorithms. In the latter, constraints in the analog circuits' precision can be offloaded to a digital signal processor. This thesis aims at the development of a methodology for the analysis, the modeling and the compensation of the analog impairments arising in different stages of a receiving chain using digital calibration techniques. Both single and multiple channel architectures are addressed exploiting the capability of the calibration algorithm to homogenize all the channels' responses of a multi-channel system in addition to the compensation of nonlinearities in each response. The systems targeted for the application of digital post compensation are a pipeline ADC, a digital-IF sub-sampling receiver and a 4-channel TI-ADC. The research focuses on post distortion methods using nonlinear dynamic models to approximate the post-inverse of the nonlinear system and to correct the distortions arising from static and dynamic errors. Volterra model is used due to its general approximation capabilities for the compensation of nonlinear systems with memory. Digital calibration is applied to a Sample and Hold and to a pipeline ADC simulated in the 45nm process, demonstrating high linearity improvement even with incomplete settling errors enabling the use of faster clock speeds. An extended model based on the baseband Volterra series is proposed and applied to the compensation of a digital-IF sub-sampling receiver. This architecture envisages frequency selectivity carried out at IF by an active band-pass CMOS filter causing in-band and out-of-band nonlinear distortions. The improved performance of the proposed model is demonstrated with circuital simulations of a 10th-order band pass filter, realized using a five-stage Gm-C Biquad cascade, and validated using out-of-sample sinusoidal and QAM signals. The same technique is extended to an array receiver with mismatched channels' responses showing that digital calibration can compensate the loss of directivity and enhance the overall system SFDR. An iterative backward pruning is applied to the Volterra models showing that complexity can be reduced without impacting linearity, obtaining state-of-the-art accuracy/complexity performance. Calibration of Time-Interleaved ADCs, widely used in RF-to-digital wideband receivers, is carried out developing ad hoc models because the steep discontinuities generated by the imperfect canceling of aliasing would require a huge number of terms in a polynomial approximation. A closed-form solution is derived for a 4-channel TI-ADC affected by gain errors and timing skews solving the perfect reconstruction equations. A background calibration technique is presented based on cyclo-stationary filter banks architecture. Convergence speed and accuracy of the recursive algorithm are discussed and complexity reduction techniques are applied

Intelligent optical methods in image analysis for human detection

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.This thesis introduces the concept of a person recognition system for use on an integrated autonomous surveillance camera. Developed to enable generic surveillance tasks without the need for complex setup procedures nor operator assistance, this is achieved through the novel use of a simple dynamic noise reduction and object detection algorithm requiring no previous knowledge of the installation environment and without any need to train the system to its installation. The combination of this initial processing stage with a novel hybrid neural network structure composed of a SOM mapper and an MLP classifier using a combination of common and individual input data lines has enabled the development of a reliable detection process, capable of dealing with both noisy environments and partial occlusion of valid targets. With a final correct classification rate of 94% on a single image analysis, this provides a huge step forwards as compared to the reported 97% failure rate of standard camera surveillance systems

Technical Design Report for the PANDA Micro Vertex Detector

This document illustrates the technical layout and the expected performance of the Micro Vertex Detector (MVD) of the PANDA experiment. The MVD will detect charged particles as close as possible to the interaction zone. Design criteria and the optimisation process as well as the technical solutions chosen are discussed and the results of this process are subjected to extensive Monte Carlo physics studies. The route towards realisation of the detector is outlined

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing