Performance evaluation of a prototyped wireless ground sensor networks

This thesis investigated the suitability of wireless, unattended ground sensor networks for military applications. The unattended aspect requires the network to self-organize and adapt to dynamic changes. A wireless, unattended ground sensor network was prototyped using commercial off-the-shelf technology and three to four networked nodes. Device and network performance were measured under indoor and outdoor scenarios. The measured communication range of a node varied between three and nineteen meters depending on the scenario. The sensors evaluated were an acoustic sensor, a magnetic sensor, and an acceleration sensor. The measured sensing range varied by the type of sensor. Node discovery durations observed were between forty seconds and over five minutes. Node density calculations indicated that the prototype was scalable to five hundred nodes. This thesis substantiated the feasibility of interconnecting, self-organizing sensor nodes in military applications. Tests and evaluations demonstrated that the network was capable of dynamic adaptation to failure and degradation.http://archive.org/details/performanceevalu109452263Approved for public release; distribution is unlimited

Test and evaluation of a prototyped sensor-camera network for persistent intelligence, surveillance, and reconnaissance in support of tactical coalition networking environments

This thesis investigated the feasibility of deploying an integrated sensor-camera network in military and law enforcement applications. The system was built using entirely commercial-off-the-shelf technologies. The prototype used the unattended ground sensors combined with digital video surveillance cameras to provide accurate real-time situational awareness, persistent intelligence and remote security. A robust testing and evaluation plan was created to measure the system's performance based on specific metrics. The tests focused primarily on the capabilities of the sensor aspect of the network. Tests were conducted to determine the maximum detection range, probabilities of detection, maximum communications range, and battery life. Mathematical models were created to assist network planners. Additionally, the prototyped system was tested through field exercises as part of the Naval Postgraduate School's Coalition Operating Area Surveillance and Targeting System field demonstrations in California and northern Thailand. Although the sensing capabilities exceeded the minimum metrics, the system was not suitable for use in military applications. However, the prototyped network would work well in less demanding law enforcement environments. Additionally, the feasibility and the need to develop an integrated sensor-camera network were demonstrated.http://archive.org/details/testndevaluation109452780US Navy (USN) author.Approved for public release; distribution is unlimited

Toward a robot swarm protecting a group of migrants

Different geopolitical conflicts of recent years have led to mass migration of several civilian populations. These migrations take place in militarized zones, indicating real danger contexts for the populations. Indeed, civilians are increasingly targeted during military assaults. Defense and security needs have increased; therefore, there is a need to prioritize the protection of migrants. Very few or no arrangements are available to manage the scale of displacement and the protection of civilians during migration. In order to increase their security during mass migration in an inhospitable territory, this article proposes an assistive system using a team of mobile robots, labeled a rover swarm that is able to provide safety area around the migrants. We suggest a coordination algorithm including CNN and fuzzy logic that allows the swarm to synchronize their movements and provide better sensor coverage of the environment. Implementation is carried out using on a reduced scale rover to enable evaluation of the functionalities of the suggested software architecture and algorithms. Results bring new perspectives to helping and protecting migrants with a swarm that evolves in a complex and dynamic environment

Experimental investigation on the use of multiple very low-cost inertial-based devices for comfort assessment and rail track monitoring

The periodic rail track inspection is mandatory to ensure ride comfort and operational safety. However, conventional monitoring technologies have high costs, stimulating research on low-cost alternatives. In this regard, this paper presents the first experimental results on the use of multiple very low-cost sensors aboard trains for vibration monitoring, proposing a collective approach to provide more accurate and robust results. Nine devices comprising commercial-grade inertial sensors were tested in different distributions aboard a high-speed track recording train. Frequency weighted accelerations were calculated in accordance with ISO 2631 standard as comfort and indirect track quality index. As expected, vertical and lateral results were correlated with, respectively, track longitudinal level (range D1, maximum correlation coefficient of 0.86) and alignment (range D2, maximum correlation coefficient of 0.60), with numerically similar results when considering the fused signal. The collective approach's potential was proven as a result of the noise reduction and the discrepant sensor identification

Sensor fusion in driving assistance systems

Mención Internacional en el título de doctorLa vida diaria en los países desarrollados y en vías de desarrollo depende en gran medida del transporte urbano y en carretera. Esta actividad supone un coste importante para sus usuarios activos y pasivos en términos de polución y accidentes, muy habitualmente debidos al factor humano. Los nuevos desarrollos en seguridad y asistencia a la conducción, llamados Advanced Driving Assistance Systems (ADAS), buscan mejorar la seguridad en el transporte, y a medio plazo, llegar a la conducción autónoma. Los ADAS, al igual que la conducción humana, están basados en sensores que proporcionan información acerca del entorno, y la fiabilidad de los sensores es crucial para las aplicaciones ADAS al igual que las capacidades sensoriales lo son para la conducción humana. Una de las formas de aumentar la fiabilidad de los sensores es el uso de la Fusión Sensorial, desarrollando nuevas estrategias para el modelado del entorno de conducción gracias al uso de diversos sensores, y obteniendo una información mejorada a partid de los datos disponibles. La presente tesis pretende ofrecer una solución novedosa para la detección y clasificación de obstáculos en aplicaciones de automoción, usando fusión vii sensorial con dos sensores ampliamente disponibles en el mercado: la cámara de espectro visible y el escáner láser. Cámaras y láseres son sensores comúnmente usados en la literatura científica, cada vez más accesibles y listos para ser empleados en aplicaciones reales. La solución propuesta permite la detección y clasificación de algunos de los obstáculos comúnmente presentes en la vía, como son ciclistas y peatones. En esta tesis se han explorado novedosos enfoques para la detección y clasificación, desde la clasificación empleando clusters de nubes de puntos obtenidas desde el escáner láser, hasta las técnicas de domain adaptation para la creación de bases de datos de imágenes sintéticas, pasando por la extracción inteligente de clusters y la detección y eliminación del suelo en nubes de puntos.Life in developed and developing countries is highly dependent on road and urban motor transport. This activity involves a high cost for its active and passive users in terms of pollution and accidents, which are largely attributable to the human factor. New developments in safety and driving assistance, called Advanced Driving Assistance Systems (ADAS), are intended to improve security in transportation, and, in the mid-term, lead to autonomous driving. ADAS, like the human driving, are based on sensors, which provide information about the environment, and sensors’ reliability is crucial for ADAS applications in the same way the sensing abilities are crucial for human driving. One of the ways to improve reliability for sensors is the use of Sensor Fusion, developing novel strategies for environment modeling with the help of several sensors and obtaining an enhanced information from the combination of the available data. The present thesis is intended to offer a novel solution for obstacle detection and classification in automotive applications using sensor fusion with two highly available sensors in the market: visible spectrum camera and laser scanner. Cameras and lasers are commonly used sensors in the scientific literature, increasingly affordable and ready to be deployed in real world applications. The solution proposed provides obstacle detection and classification for some obstacles commonly present in the road, such as pedestrians and bicycles. Novel approaches for detection and classification have been explored in this thesis, from point cloud clustering classification for laser scanner, to domain adaptation techniques for synthetic dataset creation, and including intelligent clustering extraction and ground detection and removal from point clouds.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Cristina Olaverri Monreal.- Secretario: Arturo de la Escalera Hueso.- Vocal: José Eugenio Naranjo Hernánde

Autosub Long Range 1500: A continuous 2000 km field trial

Long Range Autonomous Underwater Vehicles (LRAUVs) offer the potential to monitor the ocean at higher spatial and temporal resolutions compared to conventional ship-based techniques. The multi-week to multi-month endurance of LRAUVs enables them to operate independently of a support vessel, creating novel opportunities for ocean observation. The National Oceanography Centre’s Autosub Long Range is one of a small number of vehicles designed for a multi-month endurance. The latest iteration, Autosub Long Range 1500 (ALR1500), is a 1500 m depth-rated LRAUV developed for ocean science in coastal and shelf seas or in the epipelagic and meteorologic regions of the ocean. This paper presents the design of the ALR1500 and results from a five week continuous deployment from Plymouth, UK, to the continental shelf break and back again, a distance of approximately 2000km which consumed half of the installed energy. The LRAUV was unaccompanied throughout the mission and operated continuously beyond visual line of sight

Efficient Range-Free Monte-Carlo-Localization for Mobile Wireless Sensor Networks

Das Hauptproblem von Lokalisierungsalgorithmen für WSNs basierend auf Ankerknoten ist die Abhängigkeit von diesen. Mobilität im Netzwerk kann zu Topologien führen, in denen einzelne Knoten oder ganze Teile des Netzwerks temporär von allen Ankerknoten isoliert werden. In diesen Fällen ist keine weitere Lokalisierung möglich. Dies wirkt sich primär auf den Lokalisierungsfehler aus, der in diesen Fällen stark ansteigt. Des weiteren haben Betreiber von Sensornetzwerken Interesse daran, die Anzahl der kosten- und wartungsintensiveren Ankerknoten auf ein Minimum zu reduzieren. Dies verstärkt zusätzlich das Problem von nicht verfügbaren Ankerknoten während des Netzwerkbetriebs. In dieser Arbeit werden zunächst die Vor- und Nachteile der beiden großen Hauptkategorien von Lokalisierungsalgorithmen (range-based und range-free Verfahren) diskutiert und eine Studie eines oft für range-based Lokalisierung genutzten Distanzbestimmungsverfahren mit Hilfe des RSSI vorgestellt. Danach werden zwei neue Varianten für ein bekanntes range-free Lokalisierungsverfahren mit Namen MCL eingeführt. Beide haben zum Ziel das Problem der temporär nicht verfügbaren Ankerknoten zu lösen, bedienen sich dabei aber unterschiedlicher Mittel. SA-MCL nutzt ein dead reckoning Verfahren, um die Positionsschätzung vom letzten bekannten Standort weiter zu führen. Dies geschieht mit Hilfe von zusätzlichen Sensorinformationen, die von einem elektronischen Kompass und einem Beschleunigungsmesser zur Verfügung gestellt werden. PO-MCL hingegen nutzt das Mobilitätsverhalten von einigen Anwendungen in Sensornetzwerken aus, bei denen sich alle Knoten primär auf einer festen Anzahl von Pfaden bewegen, um den Lokalisierungsprozess zu verbessern. Beide Methoden werden durch detaillierte Netzwerksimulationen evaluiert. Im Fall von SA-MCL wird außerdem eine Implementierung auf echter Hardware vorgestellt und eine Feldstudie in einem mobilen Sensornetzwerk durchgeführt. Aus den Ergebnissen ist zu sehen, dass der Lokalisierungsfehler in Situationen mit niedriger Ankerknotendichte im Fall von SA-MCL um bis zu 60% reduziert werden kann, beziehungsweise um bis zu 50% im Fall von PO-MCL.