Wireless communication enhancement methods for mobile robots in radiation environments

En entornos hostiles tales como aquellas instalaciones científicas donde la radiación ionizante es el principal peligro, el hecho de reducir las intervenciones humanas mediante el incremento de las operaciones robotizadas está siendo cada vez más de especial interés. CERN, la Organización Europea para la Investigación Nuclear, tiene alrededor de unos 50 km de superficie subterránea donde robots móviles controlador de forma remota podrían ayudar en su funcionamiento, por ejemplo, a la hora de llevar a cabo inspecciones remotas sobre radiación en los diferentes áreas destinados al efecto. No solo es preciso considerar que los robots deben ser capaces de recorrer largas distancias y operar durante largos periodos de tiempo, sino que deben saber desenvolverse en los correspondientes túneles subterráneos, tener en cuenta la presencia de campos electromagnéticos, radiación ionizante, etc. y finalmente, el hecho de que los robots no deben interrumpir el funcionamiento de los aceleradores. El hecho de disponer de un sistema de comunicaciones inalámbrico fiable y robusto es esencial para la correcta ejecución de las misiones que los robots deben afrontar y por supuesto, para evitar tales situaciones en las que es necesario la recuperación manual de los robots al agotarse su energía o al perder el enlace de comunicaciones. El objetivo de esta Tesis es proveer de las directrices y los medios necesarios para reducir el riesgo de fallo en la misión y maximizar las capacidades de los robots móviles inalámbricos los cuales disponen de almacenamiento finito de energía al trabajar en entornos peligrosos donde no se dispone de línea de vista directa. Para ello se proponen y muestran diferentes estrategias y métodos de comunicación inalámbrica. Teniendo esto en cuenta, se presentan a continuación los objetivos de investigación a seguir a lo largo de la Tesis: predecir la cobertura de comunicaciones antes y durante las misiones robotizadas; optimizar la capacidad de red inalámbrica de los robots móviles con respecto a su posición; y mejorar el rango operacional de esta clase de robots. Por su parte, las contribuciones a la Tesis se citan más abajo. El primer conjunto de contribuciones son métodos novedosos para predecir el consumo de energía y la autonomía en la comunicación antes y después de disponer de los robots en el entorno seleccionado. Esto es importante para proporcionar conciencia de la situación del robot y evitar fallos en la misión. El consumo de energía se predice usando una estrategia propuesta la cual usa modelos de consumo provenientes de diferentes componentes en un robot. La predicción para la cobertura de comunicaciones se desarrolla usando un nuevo filtro de RSS (Radio Signal Strength) y técnicas de estimación con la ayuda de Filtros de Kalman. El segundo conjunto de contribuciones son métodos para optimizar el rango de comunicaciones usando novedosas técnicas basadas en muestreo espacial que son robustas frente a ruidos de campos de detección y radio y que proporcionan redundancia. Se emplean métodos de diferencia central finitos para determinar los gradientes 2D RSS y se usa la movilidad del robot para optimizar el rango de comunicaciones y la capacidad de red. Este método también se valida con un caso de estudio centrado en la teleoperación háptica de robots móviles inalámbricos. La tercera contribución es un algoritmo robusto y estocástico descentralizado para la optimización de la posición al considerar múltiples robots autónomos usados principalmente para extender el rango de comunicaciones desde la estación de control al robot que está desarrollando la tarea. Todos los métodos y algoritmos propuestos se verifican y validan usando simulaciones y experimentos de campo con variedad de robots móviles disponibles en CERN. En resumen, esta Tesis ofrece métodos novedosos y demuestra su uso para: predecir RSS; optimizar la posición del robot; extender el rango de las comunicaciones inalámbricas; y mejorar las capacidades de red de los robots móviles inalámbricos para su uso en aplicaciones dentro de entornos peligrosos, que como ya se mencionó anteriormente, se destacan las instalaciones científicas con emisión de radiación ionizante. En otros términos, se ha desarrollado un conjunto de herramientas para mejorar, facilitar y hacer más seguras las misiones de los robots en entornos hostiles. Esta Tesis demuestra tanto en teoría como en práctica que los robots móviles pueden mejorar la calidad de las comunicaciones inalámbricas mediante la profundización en el estudio de su movilidad para optimizar dinámicamente sus posiciones y mantener conectividad incluso cuando no existe línea de vista. Los métodos desarrollados en la Tesis son especialmente adecuados para su fácil integración en robots móviles y pueden ser aplicados directamente en la capa de aplicación de la red inalámbrica. ABSTRACT In hostile environments such as in scientific facilities where ionising radiation is a dominant hazard, reducing human interventions by increasing robotic operations are desirable. CERN, the European Organization for Nuclear Research, has around 50 km of underground scientific facilities, where wireless mobile robots could help in the operation of the accelerator complex, e.g. in conducting remote inspections and radiation surveys in different areas. The main challenges to be considered here are not only that the robots should be able to go over long distances and operate for relatively long periods, but also the underground tunnel environment, the possible presence of electromagnetic fields, radiation effects, and the fact that the robots shall in no way interrupt the operation of the accelerators. Having a reliable and robust wireless communication system is essential for successful execution of such robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy or when the robot loses its communication link. The goal of this thesis is to provide means to reduce risk of mission failure and maximise mission capabilities of wireless mobile robots with finite energy storage capacity working in a radiation environment with non-line-of-sight (NLOS) communications by employing enhanced wireless communication methods. Towards this goal, the following research objectives are addressed in this thesis: predict the communication range before and during robotic missions; optimise and enhance wireless communication qualities of mobile robots by using robot mobility and employing multi-robot network. This thesis provides introductory information on the infrastructures where mobile robots will need to operate, the tasks to be carried out by mobile robots and the problems encountered in these environments. The reporting of research work carried out to improve wireless communication comprises an introduction to the relevant radio signal propagation theory and technology followed by explanation of the research in the following stages: An analysis of the wireless communication requirements for mobile robot for different tasks in a selection of CERN facilities; predictions of energy and communication autonomies (in terms of distance and time) to reduce risk of energy and communication related failures during missions; autonomous navigation of a mobile robot to find zone(s) of maximum radio signal strength to improve communication coverage area; and autonomous navigation of one or more mobile robots acting as mobile wireless relay (repeater) points in order to provide a tethered wireless connection to a teleoperated mobile robot carrying out inspection or radiation monitoring activities in a challenging radio environment. The specific contributions of this thesis are outlined below. The first sets of contributions are novel methods for predicting the energy autonomy and communication range(s) before and after deployment of the mobile robots in the intended environments. This is important in order to provide situational awareness and avoid mission failures. The energy consumption is predicted by using power consumption models of different components in a mobile robot. This energy prediction model will pave the way for choosing energy-efficient wireless communication strategies. The communication range prediction is performed using radio signal propagation models and applies radio signal strength (RSS) filtering and estimation techniques with the help of Kalman filters and Gaussian process models. The second set of contributions are methods to optimise the wireless communication qualities by using novel spatial sampling based techniques that are robust to sensing and radio field noises and provide redundancy features. Central finite difference (CFD) methods are employed to determine the 2-D RSS gradients and use robot mobility to optimise the communication quality and the network throughput. This method is also validated with a case study application involving superior haptic teleoperation of wireless mobile robots where an operator from a remote location can smoothly navigate a mobile robot in an environment with low-wireless signals. The third contribution is a robust stochastic position optimisation algorithm for multiple autonomous relay robots which are used for wireless tethering of radio signals and thereby to enhance the wireless communication qualities. All the proposed methods and algorithms are verified and validated using simulations and field experiments with a variety of mobile robots available at CERN. In summary, this thesis offers novel methods and demonstrates their use to predict energy autonomy and wireless communication range, optimise robots position to improve communication quality and enhance communication range and wireless network qualities of mobile robots for use in applications in hostile environmental characteristics such as scientific facilities emitting ionising radiations. In simpler terms, a set of tools are developed in this thesis for improving, easing and making safer robotic missions in hostile environments. This thesis validates both in theory and experiments that mobile robots can improve wireless communication quality by exploiting robots mobility to dynamically optimise their positions and maintain connectivity even when the (radio signal) environment possess non-line-of-sight characteristics. The methods developed in this thesis are well-suited for easier integration in mobile robots and can be applied directly at the application layer of the wireless network. The results of the proposed methods have outperformed other comparable state-of-the-art methods.

Diseño y análisis de unidades didácticas para Procesado Digital de la Señal.

Este Proyecto Fin de Carrera pretende desarrollar una serie de unidades didácticas orientadas a mejorar el aprendizaje de la teoría de procesado digital de señales a través de la aplicación práctica. Con tal fin, se han diseñado una serie de prácticas que permitan al alumno alcanzar un apropiado nivel de conocimiento de la asignatura, la adquisición de competencias y alcanzar los resultados de aprendizaje previstos. Para desarrollar el proyecto primero se ha realizado una selección apropiada de los contenidos de la teoría de procesado digital de señales en relación con los resultados de aprendizaje esperados, seguidamente se han diseñado y validado unas prácticas basadas en un entorno de trabajo basado en MATLAB y DSP, y por último se ha redactado un manual de laboratorio que combina una parte teórica con su práctica correspondiente. El objetivo perseguido con la realización de estas prácticas es alcanzar un equilibrio teórico/práctico que permita sacar el máximo rendimiento de la asignatura desde el laboratorio, trabajando principalmente con el IDE Code Composer Studio junto con un kit de desarrollo basado en un DSP. ABSTRACT. This dissertation intends to develop some lessons oriented to improve about the digital signal processing theory. In order to get this objective some practices have been developed to allow to the students to achieve an appropriate level of knowledge of the subject, acquire skills and achieve the intended learning outcomes. To develop the project firstly it has been made an appropriate selection of the contents of the digital signal processing theory related with the expected results. After that, five practices based in a work environment based on Matlab and DSP have been designed and validated, and finally a laboratory manual has been drafted that combines the theoretical part with its corresponding practice. The objective with the implementation of these practices is to achieve a theoretical / practical balance to get the highest performance to the subject from the laboratory working mainly with the Code Composer Studio IDE together a development kit based on DSP.

Diseño de algoritmos de guerra electrónica y radar para su implementación en sistemas de tiempo real

Esta tesis se centra en el estudio y desarrollo de algoritmos de guerra electrónica {electronic warfare, EW) y radar para su implementación en sistemas de tiempo real. La llegada de los sistemas de radio, radar y navegación al terreno militar llevó al desarrollo de tecnologías para combatirlos. Así, el objetivo de los sistemas de guerra electrónica es el control del espectro electomagnético. Una de la funciones de la guerra electrónica es la inteligencia de señales {signals intelligence, SIGINT), cuya labor es detectar, almacenar, analizar, clasificar y localizar la procedencia de todo tipo de señales presentes en el espectro. El subsistema de inteligencia de señales dedicado a las señales radar es la inteligencia electrónica {electronic intelligence, ELINT). Un sistema de tiempo real es aquel cuyo factor de mérito depende tanto del resultado proporcionado como del tiempo en que se da dicho resultado. Los sistemas radar y de guerra electrónica tienen que proporcionar información lo más rápido posible y de forma continua, por lo que pueden encuadrarse dentro de los sistemas de tiempo real. La introducción de restricciones de tiempo real implica un proceso de realimentación entre el diseño del algoritmo y su implementación en plataformas “hardware”. Las restricciones de tiempo real son dos: latencia y área de la implementación. En esta tesis, todos los algoritmos presentados se han implementado en plataformas del tipo field programmable gate array (FPGA), ya que presentan un buen compromiso entre velocidad, coste total, consumo y reconfigurabilidad. La primera parte de la tesis está centrada en el estudio de diferentes subsistemas de un equipo ELINT: detección de señales mediante un detector canalizado, extracción de los parámetros de pulsos radar, clasificación de modulaciones y localization pasiva. La transformada discreta de Fourier {discrete Fourier transform, DFT) es un detector y estimador de frecuencia quasi-óptimo para señales de banda estrecha en presencia de ruido blanco. El desarrollo de algoritmos eficientes para el cálculo de la DFT, conocidos como fast Fourier transform (FFT), han situado a la FFT como el algoritmo más utilizado para la detección de señales de banda estrecha con requisitos de tiempo real. Así, se ha diseñado e implementado un algoritmo de detección y análisis espectral para su implementación en tiempo real. Los parámetros más característicos de un pulso radar son su tiempo de llegada y anchura de pulso. Se ha diseñado e implementado un algoritmo capaz de extraer dichos parámetros. Este algoritmo se puede utilizar con varios propósitos: realizar un reconocimiento genérico del radar que transmite dicha señal, localizar la posición de dicho radar o bien puede utilizarse como la parte de preprocesado de un clasificador automático de modulaciones. La clasificación automática de modulaciones es extremadamente complicada en entornos no cooperativos. Un clasificador automático de modulaciones se divide en dos partes: preprocesado y el algoritmo de clasificación. Los algoritmos de clasificación basados en parámetros representativos calculan diferentes estadísticos de la señal de entrada y la clasifican procesando dichos estadísticos. Los algoritmos de localization pueden dividirse en dos tipos: triangulación y sistemas cuadráticos. En los algoritmos basados en triangulación, la posición se estima mediante la intersección de las rectas proporcionadas por la dirección de llegada de la señal. En cambio, en los sistemas cuadráticos, la posición se estima mediante la intersección de superficies con igual diferencia en el tiempo de llegada (time difference of arrival, TDOA) o diferencia en la frecuencia de llegada (frequency difference of arrival, FDOA). Aunque sólo se ha implementado la estimación del TDOA y FDOA mediante la diferencia de tiempos de llegada y diferencia de frecuencias, se presentan estudios exhaustivos sobre los diferentes algoritmos para la estimación del TDOA, FDOA y localización pasiva mediante TDOA-FDOA. La segunda parte de la tesis está dedicada al diseño e implementación filtros discretos de respuesta finita (finite impulse response, FIR) para dos aplicaciones radar: phased array de banda ancha mediante filtros retardadores (true-time delay, TTD) y la mejora del alcance de un radar sin modificar el “hardware” existente para que la solución sea de bajo coste. La operación de un phased array de banda ancha mediante desfasadores no es factible ya que el retardo temporal no puede aproximarse mediante un desfase. La solución adoptada e implementada consiste en sustituir los desfasadores por filtros digitales con retardo programable. El máximo alcance de un radar depende de la relación señal a ruido promedio en el receptor. La relación señal a ruido depende a su vez de la energía de señal transmitida, potencia multiplicado por la anchura de pulso. Cualquier cambio hardware que se realice conlleva un alto coste. La solución que se propone es utilizar una técnica de compresión de pulsos, consistente en introducir una modulación interna a la señal, desacoplando alcance y resolución. ABSTRACT This thesis is focused on the study and development of electronic warfare (EW) and radar algorithms for real-time implementation. The arrival of radar, radio and navigation systems to the military sphere led to the development of technologies to fight them. Therefore, the objective of EW systems is the control of the electromagnetic spectrum. Signals Intelligence (SIGINT) is one of the EW functions, whose mission is to detect, collect, analyze, classify and locate all kind of electromagnetic emissions. Electronic intelligence (ELINT) is the SIGINT subsystem that is devoted to radar signals. A real-time system is the one whose correctness depends not only on the provided result but also on the time in which this result is obtained. Radar and EW systems must provide information as fast as possible on a continuous basis and they can be defined as real-time systems. The introduction of real-time constraints implies a feedback process between the design of the algorithms and their hardware implementation. Moreover, a real-time constraint consists of two parameters: Latency and area of the implementation. All the algorithms in this thesis have been implemented on field programmable gate array (FPGAs) platforms, presenting a trade-off among performance, cost, power consumption and reconfigurability. The first part of the thesis is related to the study of different key subsystems of an ELINT equipment: Signal detection with channelized receivers, pulse parameter extraction, modulation classification for radar signals and passive location algorithms. The discrete Fourier transform (DFT) is a nearly optimal detector and frequency estimator for narrow-band signals buried in white noise. The introduction of fast algorithms to calculate the DFT, known as FFT, reduces the complexity and the processing time of the DFT computation. These properties have placed the FFT as one the most conventional methods for narrow-band signal detection for real-time applications. An algorithm for real-time spectral analysis for user-defined bandwidth, instantaneous dynamic range and resolution is presented. The most characteristic parameters of a pulsed signal are its time of arrival (TOA) and the pulse width (PW). The estimation of these basic parameters is a fundamental task in an ELINT equipment. A basic pulse parameter extractor (PPE) that is able to estimate all these parameters is designed and implemented. The PPE may be useful to perform a generic radar recognition process, perform an emitter location technique and can be used as the preprocessing part of an automatic modulation classifier (AMC). Modulation classification is a difficult task in a non-cooperative environment. An AMC consists of two parts: Signal preprocessing and the classification algorithm itself. Featurebased algorithms obtain different characteristics or features of the input signals. Once these features are extracted, the classification is carried out by processing these features. A feature based-AMC for pulsed radar signals with real-time requirements is studied, designed and implemented. Emitter passive location techniques can be divided into two classes: Triangulation systems, in which the emitter location is estimated with the intersection of the different lines of bearing created from the estimated directions of arrival, and quadratic position-fixing systems, in which the position is estimated through the intersection of iso-time difference of arrival (TDOA) or iso-frequency difference of arrival (FDOA) quadratic surfaces. Although TDOA and FDOA are only implemented with time of arrival and frequency differences, different algorithms for TDOA, FDOA and position estimation are studied and analyzed. The second part is dedicated to FIR filter design and implementation for two different radar applications: Wideband phased arrays with true-time delay (TTD) filters and the range improvement of an operative radar with no hardware changes to minimize costs. Wideband operation of phased arrays is unfeasible because time delays cannot be approximated by phase shifts. The presented solution is based on the substitution of the phase shifters by FIR discrete delay filters. The maximum range of a radar depends on the averaged signal to noise ratio (SNR) at the receiver. Among other factors, the SNR depends on the transmitted signal energy that is power times pulse width. Any possible hardware change implies high costs. The proposed solution lies in the use of a signal processing technique known as pulse compression, which consists of introducing an internal modulation within the pulse width, decoupling range and resolution.

Cancelación activa del ruido utilizando el KIT TMS320C5515 EZDSP

El control, o cancelación activa de ruido, consiste en la atenuación del ruido presente en un entorno acústico mediante la emisión de una señal igual y en oposición de fase al ruido que se desea atenuar. La suma de ambas señales en el medio acústico produce una cancelación mutua, de forma que el nivel de ruido resultante es mucho menor al inicial. El funcionamiento de estos sistemas se basa en los principios de comportamiento de los fenómenos ondulatorios descubiertos por Augustin-Jean Fresnel, Christiaan Huygens y Thomas Young entre otros. Desde la década de 1930, se han desarrollado prototipos de sistemas de control activo de ruido, aunque estas primeras ideas eran irrealizables en la práctica o requerían de ajustes manuales cada poco tiempo que hacían inviable su uso. En la década de 1970, el investigador estadounidense Bernard Widrow desarrolla la teoría de procesado adaptativo de señales y el algoritmo de mínimos cuadrados LMS. De este modo, es posible implementar filtros digitales cuya respuesta se adapte de forma dinámica a las condiciones variables del entorno. Con la aparición de los procesadores digitales de señal en la década de 1980 y su evolución posterior, se abre la puerta para el desarrollo de sistemas de cancelación activa de ruido basados en procesado de señal digital adaptativo. Hoy en día, existen sistemas de control activo de ruido implementados en automóviles, aviones, auriculares o racks de equipamiento profesional. El control activo de ruido se basa en el algoritmo fxlms, una versión modificada del algoritmo LMS de filtrado adaptativo que permite compensar la respuesta acústica del entorno. De este modo, se puede filtrar una señal de referencia de ruido de forma dinámica para emitir la señal adecuada que produzca la cancelación. Como el espacio de cancelación acústica está limitado a unas dimensiones de la décima parte de la longitud de onda, sólo es viable la reducción de ruido en baja frecuencia. Generalmente se acepta que el límite está en torno a 500 Hz. En frecuencias medias y altas deben emplearse métodos pasivos de acondicionamiento y aislamiento, que ofrecen muy buenos resultados. Este proyecto tiene como objetivo el desarrollo de un sistema de cancelación activa de ruidos de carácter periódico, empleando para ello electrónica de consumo y un kit de desarrollo DSP basado en un procesador de muy bajo coste. Se han desarrollado una serie de módulos de código para el DSP escritos en lenguaje C, que realizan el procesado de señal adecuado a la referencia de ruido. Esta señal procesada, una vez emitida, produce la cancelación acústica. Empleando el código implementado, se han realizado pruebas que generan la señal de ruido que se desea eliminar dentro del propio DSP. Esta señal se emite mediante un altavoz que simula la fuente de ruido a cancelar, y mediante otro altavoz se emite una versión filtrada de la misma empleando el algoritmo fxlms. Se han realizado pruebas con distintas versiones del algoritmo, y se han obtenido atenuaciones de entre 20 y 35 dB medidas en márgenes de frecuencia estrechos alrededor de la frecuencia del generador, y de entre 8 y 15 dB medidas en banda ancha. ABSTRACT. Active noise control consists on attenuating the noise in an acoustic environment by emitting a signal equal but phase opposed to the undesired noise. The sum of both signals results in mutual cancellation, so that the residual noise is much lower than the original. The operation of these systems is based on the behavior principles of wave phenomena discovered by Augustin-Jean Fresnel, Christiaan Huygens and Thomas Young. Since the 1930’s, active noise control system prototypes have been developed, though these first ideas were practically unrealizable or required manual adjustments very often, therefore they were unusable. In the 1970’s, American researcher Bernard Widrow develops the adaptive signal processing theory and the Least Mean Squares algorithm (LMS). Thereby, implementing digital filters whose response adapts dynamically to the variable environment conditions, becomes possible. With the emergence of digital signal processors in the 1980’s and their later evolution, active noise cancellation systems based on adaptive signal processing are attained. Nowadays active noise control systems have been successfully implemented on automobiles, planes, headphones or racks for professional equipment. Active noise control is based on the fxlms algorithm, which is actually a modified version of the LMS adaptive filtering algorithm that allows compensation for the acoustic response of the environment. Therefore it is possible to dynamically filter a noise reference signal to obtain the appropriate cancelling signal. As the noise cancellation space is limited to approximately one tenth of the wavelength, noise attenuation is only viable for low frequencies. It is commonly accepted the limit of 500 Hz. For mid and high frequencies, conditioning and isolating passive techniques must be used, as they produce very good results. The objective of this project is to develop a noise cancellation system for periodic noise, by using consumer electronics and a DSP development kit based on a very-low-cost processor. Several C coded modules have been developed for the DSP, implementing the appropriate signal processing to the noise reference. This processed signal, once emitted, results in noise cancellation. The developed code has been tested by generating the undesired noise signal in the DSP. This signal is emitted through a speaker simulating the noise source to be removed, and another speaker emits an fxlms filtered version of the same signal. Several versions of the algorithm have been tested, obtaining attenuation levels around 20 – 35 dB measured in a tight bandwidth around the generator frequency, or around 8 – 15 dB measured in broadband.

Olfactory transduction is intrinsically noisy.

The sources of noise that limit olfactory signal detection were investigated in dissociated rat olfactory receptor cells. Near-threshold odorant-evoked currents exhibited large random fluctuation. However, similar fluctuations were observed in the absence of applied odorants when currents were induced by elevating the intracellular cyclic AMP concentration. This suggests that the fluctuations reflect noise intrinsic to the transduction mechanism, rather than the quantal nature of an odorant stimulus. For many odorants, this intrinsic noise may preclude the reliable detection of single odorant molecules.

Blind multiuser receiver for DS-CDMA wireless system

We consider blind signal detection in an asynchronous code-division multiple-access (CDMA) system employing short spreading sequences in the presence of unknown multipath fading. This approach is capable of countering the presence of multiple-access interference (MAI) in CDMA fading channels. The proposed blind multiuser detector is based on an independent component analysis (ICA) to mitigate both MAI and noise. This algorithm has been utilised in blind source separation (BSS) of unknown sources from their mixtures. It can also be used for estimating the basis vectors of BSS. The aim is to include an ICA algorithm within a wireless receiver in order to reduce the level of interference in wideband systems. This blind multiuser detector requires no training sequence compared with the conventional multiuser detection receiver. The proposed ICA blind multiuser detector is made robust with respect to knowledge of signature waveforms and the timing of the user of interest. Several experiments are performed in order to verify the validity of the proposed ICA algorithm.

Performance analysis using equivariant kernel density estimator in nonlinear mixture

This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.

Improved message passing for inference in densely connected systems

An improved inference method for densely connected systems is presented. The approach is based on passing condensed messages between variables, representing macroscopic averages of microscopic messages. We extend previous work that showed promising results in cases where the solution space is contiguous to cases where fragmentation occurs. We apply the method to the signal detection problem of Code Division Multiple Access (CDMA) for demonstrating its potential. A highly efficient practical algorithm is also derived on the basis of insight gained from the analysis. © EDP Sciences.

Discriminating depth in corrugated stereo surfaces: facilitation by a pedestal is explained by removal of uncertainty

With luminance gratings, psychophysical thresholds for detecting a small increase in the contrast of a weak ‘pedestal’ grating are 2–3 times lower than for detection of a grating when the pedestal is absent. This is the ‘dipper effect’ – a reliable improvement whose interpretation remains controversial. Analogies between luminance and depth (disparity) processing have attracted interest in the existence of a ‘disparity dipper’. Are thresholds for disparity modulation (corrugated surfaces), facilitated by the presence of a weak disparity-modulated pedestal? We used a 14-bit greyscale to render small disparities accurately, and measured 2AFC discrimination thresholds for disparity modulation (0.3 or 0.6 c/deg) of a random texture at various pedestal levels. In the first experiment, a clear dipper was found. Thresholds were about 2× lower with weak pedestals than without. But here the phase of modulation (0 or 180 deg) was varied from trial to trial. In a noisy signal-detection framework, this creates uncertainty that is reduced by the pedestal, which thus improves performance. When the uncertainty was eliminated by keeping phase constant within sessions, the dipper effect was weak or absent. Monte Carlo simulations showed that the influence of uncertainty could account well for the results of both experiments. A corollary is that the visual depth response to small disparities is probably linear, with no threshold-like nonlinearity.

Discriminating depth in stereo surfaces: dipper effect found, and lost

Measurement of detection and discrimination thresholds yields information about visual signal processing. For luminance contrast, we are 2 - 3 times more sensitive to a small increase in the contrast of a weak 'pedestal' grating, than when the pedestal is absent. This is the 'dipper effect' - a reliable improvement whose interpretation remains controversial. Analogies between luminance and depth (disparity) processing have attracted interest in the existence of a 'disparity dipper' - are thresholds for disparity, or disparity modulation (corrugated surfaces), facilitated by the presence of a weak pedestal? Lunn and Morgan (1997 Journal of the Optical Society of America A 14 360 - 371) found no dipper for disparity-modulated gratings, but technical limitations (8-bit greyscale) might have prevented the necessary measurement of very small disparity thresholds. We used a true 14-bit greyscale to render small disparities accurately, and measured 2AFC discrimination thresholds for disparity modulation (0.6 cycle deg-1) of a random texture at various pedestal levels. Which interval contained greater modulation of depth? In the first experiment, a clear dipper was found. Thresholds were about 2X1 lower with weak pedestals than without. But here the phase of modulation (0° or 180°) was randomised from trial to trial. In a noisy signal-detection framework, this creates uncertainty that is reduced by the pedestal, thus improving performance. When the uncertainty was eliminated by keeping phase constant within sessions, the dipper effect disappeared, confirming Lunn and Morgan's result. The absence of a dipper, coupled with shallow psychometric slopes, suggests that the visual response to small disparities is essentially linear, with no threshold-like nonlinearity.

Contrast discrimination and pattern masking: contrast gain control with fixed additive noise

We studied the visual mechanisms that serve to encode spatial contrast at threshold and supra-threshold levels. In a 2AFC contrast-discrimination task, observers had to detect the presence of a vertical 1 cycle deg-1 test grating (of contrast dc) that was superimposed on a similar vertical 1 cycle deg-1 pedestal grating, whereas in pattern masking the test grating was accompanied by a very different masking grating (horizontal 1 cycle deg-1, or oblique 3 cycles deg-1). When expressed as threshold contrast (dc at 75% correct) versus mask contrast (c) our results confirm previous ones in showing a characteristic 'dipper function' for contrast discrimination but a smoothly increasing threshold for pattern masking. However, fresh insight is gained by analysing and modelling performance (p; percent correct) as a joint function of (c, dc) - the performance surface. In contrast discrimination, psychometric functions (p versus logdc) are markedly less steep when c is above threshold, but in pattern masking this reduction of slope did not occur. We explored a standard gain-control model with six free parameters. Three parameters control the contrast response of the detection mechanism and one parameter weights the mask contrast in the cross-channel suppression effect. We assume that signal-detection performance (d') is limited by additive noise of constant variance. Noise level and lapse rate are also fitted parameters of the model. We show that this model accounts very accurately for the whole performance surface in both types of masking, and thus explains the threshold functions and the pattern of variation in psychometric slopes. The cross-channel weight is about 0.20. The model shows that the mechanism response to contrast increment (dc) is linearised by the presence of pedestal contrasts but remains nonlinear in pattern masking.

Inference by replication in densely connected systems

An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a large number of replicated variable systems exposed to the same evidential nodes. An assumption about the symmetry of the solutions is required for carrying out the averages; here we extend the previous derivation based on a replica-symmetric- (RS)-like structure to include a more complex one-step replica-symmetry-breaking-like (1RSB-like) ansatz. To demonstrate the potential of the approach it is employed for studying critical properties of the Ising linear perceptron and for multiuser detection in code division multiple access (CDMA) under different noise models. Results obtained under the RS assumption in the noncritical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also observed. While the 1RSB ansatz is not required for the original problems, it was applied to the CDMA signal detection problem with a more complex noise model that exhibits RSB behavior, resulting in an improvement in performance. © 2007 The American Physical Society.

Direction Finding Estimators of Cyclostationary Signals in Array Processing for Microwave Power Transmission

A solar power satellite is paid attention to as a clean, inexhaustible large- scale base-load power supply. The following technology related to beam control is used: A pilot signal is sent from the power receiving site and after direction of arrival estimation the beam is directed back to the earth by same direction. A novel direction-finding algorithm based on linear prediction technique for exploiting cyclostationary statistical information (spatial and temporal) is explored. Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or baud rates. The problem was solved by using both cyclic second-order statistics and cyclic higher-order statistics. By evaluating the corresponding cyclic statistics of the received data at certain cycle frequencies, we can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other co-channel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. The proposed algorithms employ cyclic higher-order statistics of the array output and suppress additive Gaussian noise of unknown spectral content, even when the noise shares common cycle frequencies with the non-Gaussian signals of interest. The proposed method completely exploits temporal information (multiple lag ), and also can correctly estimate direction of arrival of desired signals by suppressing undesired signals. Our approach was generalized over direction of arrival estimation of cyclostationary coherent signals. In this paper, we propose a new approach for exploiting cyclostationarity that seems to be more advanced in comparison with the other existing direction finding algorithms.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Nonlinear fiber gyroscope for quantum metrology

We examine the performance of a nonlinear fiber gyroscope for improved signal detection beating the quantum limits of its linear counterparts. The performance is examined when the nonlinear gyroscope is illuminated by practical field states, such as coherent and quadrature squeezed states. This is compared with the case of more ideal probes such as photon-number states.