Time-based Location Techniques Using Inexpensive, Unsynchronized Clocks in Wireless Networks

The ability to measure location using time of flight in IEEE 802.11 networks is impeded by the standard clock resolution, imprecise synchronization of the 802.11 protocol, and the inaccuracy of available clocks. To achieve real-time location with accuracy goals of a few meters, we derive new consensus synchronization techniques for free-running clocks. Using consensus synchronization, we improve existing time of arrival (TOA) techniques and introduce new time difference of arrival (TDOA) techniques. With this common basis, we show how TOA is theoretically superior to TDOA. Using TOA measurements, we can locate wireless nodes that participate in the location system, and using TDOA measurements, we can locate nodes that do not participate. We demonstrate applications using off-the-shelf 802.11 hardware that can determine location to within 3m using simple, existing optimization methods. The synchronization techniques extend existing ones providing distributed synchronization for free-running clocks to cases where send times cannot be controlled and adjusted precisely, as in 802.11 networks. These location and synchronization techniques may be applied to transmitting wireless nodes using any communication protocol where cooperating nodes can produce send and receive timestamps

A Sub-Terahertz Sliding Correlator Channel Sounder with Absolute Timing using Precision Time Protocol over Wi-Fi

Radio channels at mmWave and sub-THz frequencies for 5G and 6G communications offer large channel bandwidths (hundreds of MHz to several GHz) to achieve multi-Gbps data rates. Accurate modeling of the radio channel for these wide bandwidths requires capturing the absolute timing of multipath component (MPC) propagation delays with sub-nanosecond accuracy. Achieving such timing accuracy is challenging due to clock drift in untethered transmitter (TX) and receiver (RX) clocks used in time-domain channel sounders, yet will become vital in many future 6G applications. This paper proposes a novel solution utilizing precision time protocol (PTP) and periodic drift correction to achieve absolute timing for MPCs in power delay profiles (PDPs) --captured as discrete samples using sliding correlation channel sounders. Two RaspberryPi computers are programmed to implement PTP over a dedicated Wi-Fi link and synchronize the TX and RX Rubidium clocks continuously every second. This synchronization minimizes clock drift, reducing PDP sample drift to 150 samples/hour, compared to several thousand samples/hour without synchronization. Additionally, a periodic drift correction algorithm is applied to eliminate PDP sample drift and achieve sub-nanosecond timing accuracy for MPC delays. The achieved synchronicity eliminates the need for tedious and sometimes inaccurate ray tracing to synthesize omnidirectional PDPs from directional measurements. The presented solution shows promise in myriad applications, including precise position location and distributed systems that require sub-nanosecond timing accuracy and synchronization among components.Comment: 6 pages, 7 figures, 3 tables, IEEE Global Communications Conference (GLOBECOM) 202

Modeling and Monitoring of the Dynamic Response of Railroad Bridges using Wireless Smart Sensors

Railroad bridges form an integral part of railway infrastructure in the USA, carrying approximately 40 % of the ton-miles of freight. The US Department of Transportation (DOT) forecasts current rail tonnage to increase up to 88 % by 2035. Within the railway network, a bridge occurs every 1.4 miles of track, on average, making them critical elements. In an effort to accommodate safely the need for increased load carrying capacity, the Federal Railroad Association (FRA) announced a regulation in 2010 that the bridge owners must conduct and report annual inspection of all the bridges. The objective of this research is to develop appropriate modeling and monitoring techniques for railroad bridges toward understanding the dynamic responses under a moving train. To achieve the research objective, the following issues are considered specifically. For modeling, a simple, yet effective, model is developed to capture salient features of the bridge responses under a moving train. A new hybrid model is then proposed, which is a flexible and efficient tool for estimating bridge responses for arbitrary train configurations and speeds. For monitoring, measured field data is used to validate the performance of the numerical model. Further, interpretation of the proposed models showed that those models are efficient tools for predicting response of the bridge, such as fatigue and resonance. Finally, fundamental software, hardware, and algorithm components are developed for providing synchronized sensing for geographically distributed networks, as can be found in railroad bridges. The results of this research successfully demonstrate the potentials of using wirelessly measured data to perform model development and calibration that will lead to better understanding the dynamic responses of railroad bridges and to provide an effective tool for prediction of bridge response for arbitrary train configurations and speeds.National Science Foundation Grant No. CMS-0600433National Science Foundation Grant No. CMMI-0928886National Science Foundation Grant No. OISE-1107526National Science Foundation Grant No. CMMI- 0724172 (NEESR-SD)Federal Railroad Administration BAA 2010-1 projectOpe

PASSIVE TIME SYNCHRONIZATION IN SENSOR NETWORKS USING OPPORTUNISTIC FM RADIO SIGNALS

ABSTRACT Time synchronization is a critical piece of infrastructure for any wireless sensor network. It is necessary for applications such as audio localization, beam-forming, velocity calculation, and duplicate event detection. All of which require the coordination of multiple nodes. Recent advances in low-cost, low-power wireless sensors have led to an increased interest in large-scale networks of small, wireless, low-power sensor nodes. Because of the more stringent power and cost requirements that this technology is driving, current time synchronization techniques must be updated to capitalize on these advances. One time synchronization method developed specifically for wireless sensor networks is Reference Broadcast Synchronization. In RBS, a reference broadcast is transmitted to sensor nodes that require synchronization. Be recording the time of arrival, nodes can then use those time stamps to synchronize with each other. This project aimed to make the RBS system even more robust, energy efficient, and cost effective by replacing the reference broadcast with an ambient RF signal (FM, TV, AM, or satellite signals) already prevalent in the environment. The purpose of this project was to demonstrate the viability of using Opportunistic RF synchronization by 1.) quantifying error, 2.) applying this synchronization method in a real world application, and 3.), implementing a wireless sensor network using Android smart phones as sensor nodes. Many of the objectives for the project were successfully completed. For convenience and economic reasons, an FM signal was chosen as the reference broadcast. FM Radio Synchronization error was then quantified using local FM Radio stations. The results of this experiment were very favorable. Using 5 second segments for correlation, total error was found to be 0.208±4.499μs. Using 3 second segments, average error was 2.33 ± 6.784μs. Using 400ms segments, synchronization error was calculated to be 4.76 ± 8.835μs. These results were comparable to sync errors of methods currently in widespread use. It was also shown that Opportunistic RF Synchronization could be used in real world applications as well. Again FM was the RF signal of choice. FM Radio Synchronization was tested in an Audio Localization experiment with favorable results. Implementation of an Android Wireless Sensor Network according to our specifications, however, could not be achieved. HTC EVO 4G’s were programmed to communicate through TCP / IP network connections, record audio with a microphone, and to record FM Radio streams from the EVO’s internal FM radio. Although recording these two sources separately as different data tracks was successful, simultaneous recording of these streams could not be accomplished (simultaneous recording is essential for Opportunistic RF Synchronization). Although the Android smart phone implementation was not a total success, this project still provided data that supported the practical use of Opportunistic RF Synchronization.AFRLNo embarg

TIME SYNCHRONIZATION FOR TIME OF ARRIVAL BASED LOCALIZATION

ABSTRAC

Ambient Sound-Based Collaborative Localization of Indeterministic Devices

Localization is essential in wireless sensor networks. To our knowledge, no prior work has utilized low-cost devices for collaborative localization based on only ambient sound, without the support of local infrastructure. The reason may be the fact that most low-cost devices are indeterministic and suffer from uncertain input latencies. This uncertainty makes accurate localization challenging. Therefore, we present a collaborative localization algorithm (Cooperative Localization on Android with ambient Sound Sources (CLASS)) that simultaneously localizes the position of indeterministic devices and ambient sound sources without local infrastructure. The CLASS algorithm deals with the uncertainty by splitting the devices into subsets so that outliers can be removed from the time difference of arrival values and localization results. Since Android is indeterministic, we select Android devices to evaluate our approach. The algorithm is evaluated with an outdoor experiment and achieves a mean Root Mean Square Error (RMSE) of 2.18 m with a standard deviation of 0.22 m. Estimated directions towards the sound sources have a mean RMSE of 17.5 ° and a standard deviation of 2.3 °. These results show that it is feasible to simultaneously achieve a relative positioning of both devices and sound sources with sufficient accuracy, even when using non-deterministic devices and platforms, such as Android

Modeling and monitoring of the dynamic response of railroad bridges using wireless smart sensors

Railroad bridges form an integral part of railway infrastructure in the USA carrying approximately 40 % of the ton-miles of freight. The US Department of Transportation (DOT) forecasts current rail tonnage to increase up to 88 % by 2035. Within the railway network, a bridge occurs every 1.4 miles of track, on average, making them critical elements. In an effort to accommodate safely the need for increased load carrying capacity, the Federal Railroad Association (FRA) announced a regulation in 2010 that the bridge owners must report annual inspection of all the bridges. Until now, visual inspection has been the most prevalent practice in monitoring this infrastructure, while high-cost and unreliability can limit the efficiency and accuracy of such assessments. With recent advances in sensing technology, structural health monitoring can be a promising solution for providing a reliable and inexpensive ways for assessing the bridges. Nonetheless, because damage is a local phenomenon, to be able to detect/ monitor existing/potential damage, densely deployed sensors are required, which is inefficient and still expensive. Alternatively, model-based monitoring strategies can be adopted to identify a critical element from a numerical model that has been calibrated with measured field data. However, this approach has been widely adopted and applied for highway bridges, while railroad bridges have received comparably less attention. The main reason for the limited number of studies is due, in part, to fundamental differences between the loading being applied to highway bridges and railroad bridges. Usually, the mass of the vehicles crossing highway bridges is assumed to be relatively small compared to the mass of the bridge itself; as a result, the mass of the vehicles are often neglecting in the problem. In contrast, the mass of a train crossing a railroad bridge can be as large as the mass of the bridge itself. Moreover, trains are typically composed of an engine, followed by multiple cars resulting in a nearly deterministic moving mass/load being applied to the bridge that varies with speed. As a consequence, numerous models have been developed to understand the dynamic response of bridges under in-service train loads, but most fail to provide a simple, yet flexible, representation of the salient features of the responses of the bridge. The objective of this research is to develop appropriate modeling and monitoring techniques for railroad bridges toward understanding the dynamic responses under a moving train. To achieve the research objective, the following issues are considered specifically. For modeling, a simple, yet effective, model is developed to capture salient features of the bridge responses under a moving train. A new hybrid model is then proposed, which is a flexible and efficient tool for estimating bridge responses for arbitrary train configurations and speeds. For monitoring, measured field data is used to validate the performance of the numerical model. Further, interpretation of the proposed models showed that those models are efficient tools for predicting response of the bridge under undesirable and local phenomena, such as fatigue and resonance. Finally, fundamental software, hardware, and algorithm components are developed for providing synchronized sensing for geographically distributed networks, as can be found in railroad bridges. The results of this research successfully demonstrate the potentials of using wirelessly measured data to perform model development and calibration that will lead to better understanding the dynamic responses of railroad bridges and to provide an effective tool for prediction of bridge response for arbitrary train configurations and speeds.Ope

Forwarding fault detection in wireless community networks

Wireless community networks (WCN) are specially vulnerable to routing forwarding failures because of their intrinsic characteristics: use of inexpensive hardware that can be easily accessed; managed in a decentralized way, sometimes by non-expert administrators, and open to everyone; making it prone to hardware failures, misconfigurations and malicious attacks. To increase routing robustness in WCN, we propose a detection mechanism to detect faulty routers, so that the problem can be tackled. Forwarding fault detection can be explained as a 4 steps process: first, there is the need of monitoring and summarizing the traffic observed; then, the traffic summaries are shared among peers, so that evaluation of a router's behavior can be done by analyzing all the relevant traffic summaries; finally, once the faulty nodes have been detected a response mechanism is triggered to solve the issue. The contributions of this thesis focus on the first three steps of this process, providing solutions adapted to Wireless Community Networks that can be deployed without the need of modifying its current network stack. First, we study and characterize the distribution of the error of sketches, a traffic summary function that is resilient to packet dropping, modification and creation and provides better estimations than sampling. We define a random process to describe the estimation for each sketch type, which allows us to provide tighter bounds on the sketch accuracy and choose the size of the sketch more accurately for a set of given requirements on the estimation accuracy. Second, we propose KDet, a traffic summary dissemination and detection protocol that, unlike previous solutions, is resilient to collusion and false accusation without the need of knowing a packet's path. Finally, we consider the case of nodes with unsynchronized clocks and we propose a traffic validation mechanism based on sketches that is capable of discerning between faulty and non-faulty nodes even when the traffic summaries are misaligned, i.e. they refer to slightly different intervals of time.Las redes comunitarias son especialmente vulnerables a errores en la retransmisión de paquetes de red, puesto que están formadas por equipos de gama baja, que pueden ser fácilmente accedidos por extraños; están gestionados de manera distribuida y no siempre por expertos, y además están abiertas a todo el mundo; con lo que de manera habitual presentan errores de hardware o configuración y son sensibles a ataques maliciosos. Para mejorar la robustez en el enrutamiento en estas redes, proponemos el uso de un mecanismo de detección de routers defectuosos, para así poder corregir el problema. La detección de fallos de enrutamiento se puede explicar como un proceso de 4 pasos: el primero es monitorizar el tráfico existente, manteniendo desde cada punto de observación un resumen sobre el tráfico observado; después, estos resumenes se comparten entre los diferentes nodos, para que podamos llevar a cabo el siguiente paso: la evaluación del comportamiento de cada nodo. Finalmente, una vez hemos detectado los nodos maliciosos o que fallan, debemos actuar con un mecanismo de respuesta que corrija el problema. Esta tesis se concentra en los tres primeros pasos, y proponemos una solución para cada uno de ellos que se adapta al contexto de las redes comunitarias, de tal manera que se puede desplegar en ellas sin la necesidad de modificar los sistemas y protocolos de red ya existentes. Respecto a los resumenes de tráfico, presentamos un estudio y caracterización de la distribución de error de los sketches, una estructura de datos que es capaz de resumir flujos de tráfico resistente a la pérdida, manipulación y creación de paquetes y que además tiene mejor resolución que el muestreo. Para cada tipo de sketch, definimos una función de distribución que caracteriza el error cometido, de esta manera somos capaces de determinar con más precisión el tamaño del sketch requerido bajo unos requisitos de falsos positivos y negativos. Después proponemos KDet, un protocolo de diseminación de resumenes de tráfico y detección de nodos erróneos que, a diferencia de protocolos propuestos anteriormente, no require conocer el camino de cada paquete y es resistente a la confabulación de nodos maliciosos. Por último, consideramos el caso de nodos con relojes desincronizados, y proponemos un mecanismo de detección basado en sketches, capaz de discernir entre los nodos erróneos y correctos, aún a pesar del desalineamiento de los sketches (es decir, a pesar del que estos se refieran a momentos de tiempo ligeramente diferentes)