Waveform-independent frame-timing acquisition for UWB signals

In this paper, the problem of frame-level symboltiming acquisition for UWB signals is addressed. The main goalis the derivation of a frame-level timing estimator which does notrequire any prior knowledge of neither the transmitted symbolsnor the received template waveform. The independence withrespect to the received waveform is of special interest in UWBcommunication systems, where a fast and accurate estimation ofthe end-to-end channel response is a challenging and computationallydemanding task. The proposed estimator is derived under theunconditional maximum likelihood criterion, and because of thelow power of UWB signals, the low-SNR assumption is adopted. Asa result, an optimal frame-level timing estimator is derived whichoutperforms existing acquisition methods in low-SNR scenarios.

Signal Processing Techniques for Chipless UWB RFID Thermal Threshold Detector Detection.

This letter presents signal processing techniques to detect a passive thermal threshold detector based on a chipless time-domain ultrawideband (UWB) radio frequency identification (RFID) tag. The tag is composed by a UWB antenna connected to a transmission line, in turn loaded with a biomorphic thermal switch. The working principle consists of detecting the impedance change of the thermal switch. This change occurs when the temperature exceeds a threshold. A UWB radar is used as the reader. The difference between the actual time sample and a reference signal obtained from the averaging of previous samples is used to determine the switch transition and to mitigate the interferences derived from clutter reflections. A gain compensation function is applied to equalize the attenuation due to propagation loss. An improved method based on the continuous wavelet transform with Morlet wavelet is used to overcome detection problems associated to a low signal-to-noise ratio at the receiver. The average delay profile is used to detect the tag delay. Experimental measurements up to 5 m are obtained.

A planar UWB antenna with signal rejection capability in the 4-6 GHz band

The design of a compact planar antenna featuring ultra wideband performance and simultaneous signal rejection in the 4-6 GHz band, assigned for IEEE802.11a and HIPERLAN/2, is presented. The design is demonstrated assuming RT6010LM substrate with a relative dielectric constant of 10.2 and thickness of 0.64 mm. The presented results show that the designed antenna of 27 mm * 20 mm dimensions has a bandwidth from 2.7 GHz to more than 10 GHz excluding the rejection band. The antenna features near omnidirectional characteristics and good radiation efficiency.

Digitally programmable delay-locked-loop with adaptive charge pump current for UWB radar system

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

SIR performance evaluation of MB-OFDM UWB system with residual timing offset

Signal-to-interference ratio (SIR) performance of a multiband orthogonal frequency division multiplexing ultra-wideband system with residual timing offset is investigated. To do so, an exact mathematical derivation of the SIR of this system is derived. It becomes obvious that, unlike a cyclic prefixing based system, a zero padding based system is sensitive to residual timing offset.

Experimental characterization of backscattering properties of UWB antennas in the presence of close objects

RTLS and RFID systems are becoming more and more important in several fields. When these systems meet the UWB technology, they can take advantage of each other strengths. Since nowadays a strong importance is given to the "green" technology, we chose to adopt a passive solution. In this case the backscattering modulation can be used to carry data. Therefore it is necessary to analyze the behavior of the antennas used as tags, when they are closed to dierent material objects. In particular, the antenna mode part has been deeply observed, as it is the crucial part of the signal regarding the backscatter modulation.

Antipodal random sequences with prescribed second-order statistics: application to Compressive Sensing and UWB system based on DS-CDMA

It is usual to hear a strange short sentence: «Random is better than...». Why is randomness a good solution to a certain engineering problem? There are many possible answers, and all of them are related to the considered topic. In this thesis I will discuss about two crucial topics that take advantage by randomizing some waveforms involved in signals manipulations. In particular, advantages are guaranteed by shaping the second order statistic of antipodal sequences involved in an intermediate signal processing stages. The first topic is in the area of analog-to-digital conversion, and it is named Compressive Sensing (CS). CS is a novel paradigm in signal processing that tries to merge signal acquisition and compression at the same time. Consequently it allows to direct acquire a signal in a compressed form. In this thesis, after an ample description of the CS methodology and its related architectures, I will present a new approach that tries to achieve high compression by design the second order statistics of a set of additional waveforms involved in the signal acquisition/compression stage. The second topic addressed in this thesis is in the area of communication system, in particular I focused the attention on ultra-wideband (UWB) systems. An option to produce and decode UWB signals is direct-sequence spreading with multiple access based on code division (DS-CDMA). Focusing on this methodology, I will address the coexistence of a DS-CDMA system with a narrowband interferer. To do so, I minimize the joint effect of both multiple access (MAI) and narrowband (NBI) interference on a simple matched filter receiver. I will show that, when spreading sequence statistical properties are suitably designed, performance improvements are possible with respect to a system exploiting chaos-based sequences minimizing MAI only.

Generation of an UWB monocycle employing cross-phase modulation in a SOA-MZ interferometer

In the present article, an innovative approach for generation of an UWB monocycle is proposed and experimentally demonstrated. The proposed design features the combination of an interferometric device (SOA-Mach Zehnder interferometer) with an optical processor unit. The fusion of such components permits to generate, combine and customize UWB pulses. An optical pulse is used as pump signal and two optical carriers represent and the optical input of the system. The selection of a specific wavelength and therefore of a particular port provides the possibility of modifying the systems output pulse polarity. The capacity of transmitting several data sequence has been also evidenced.

Bipolar Tribocharging Signal During Friction Force Fluctuations At Metal-insulator Interfaces.

Friction and triboelectrification of materials show a strong correlation during sliding contacts. Friction force fluctuations are always accompanied by two tribocharging events at metal-insulator [e.g., polytetrafluoroethylene (PTFE)] interfaces: injection of charged species from the metal into PTFE followed by the flow of charges from PTFE to the metal surface. Adhesion maps that were obtained by atomic force microscopy (AFM) show that the region of contact increases the pull-off force from 10 to 150 nN, reflecting on a resilient electrostatic adhesion between PTFE and the metallic surface. The reported results suggest that friction and triboelectrification have a common origin that must be associated with the occurrence of strong electrostatic interactions at the interface.

Theory of small-signal ac response of a dielectric liquid containing two groups of ions

The analysis of Macdonald for electrolytes is generalized to the case in which two groups of ions are present. We assume that the electrolyte can be considered as a dispersion of ions in a dielectric liquid, and that the ionic recombination can be neglected. We present the differential equations governing the ionic redistribution when the liquid is subjected to an external electric field, describing the simultaneous diffusion of the two groups of ions in the presence of their own space charge fields. We investigate the influence of the ions on the impedance spectroscopy of an electrolytic cell. In the analysis, we assume that each group of ions have equal mobility, the electrodes perfectly block and that the adsorption phenomena can be neglected. In this framework, it is shown that the real part of the electrical impedance of the cell has a frequency dependence presenting two plateaux, related to a type of ambipolar and free diffusion coefficients. The importance of the considered problem on the ionic characterization performed by means of the impedance spectroscopy technique was discussed. (c) 2008 American Institute of Physics.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.