Isaac Amundson

A survey on localization for mobile wireless sensor networks

Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

OASiS: A Programming Framework for Service-Oriented Sensor Networks

Wireless sensor networks consist of small, inexpensive devices which interact with the environment, communicate with each other, and perform distributed computations in order to monitor spatio-temporal phenomena. These devices are ideally suited for a variety of applications including object tracking, environmental monitoring, and homeland security. At present, sensor network technologies do not provide off-the-shelf solutions to users who lack low-level network programming experience. Because of limited resources, ad hoc deployments, and volatile wireless communication links, the development of distributed applications require the combination of both application and system-level logic. Programming frameworks and middleware for traditional distributed computing are not suitable for many of these problems due to the resource constraints and interactions with the physical world. To address these challenges we have developed OASiS, a programming framework that provides abstractions for object-centric, ambient-aware, service-oriented sensor network applications. OASiS uses a well-defined model of computation based on globally asynchronous locally synchronous dataflow, and is complemented by a user-friendly modeling environment. Applications are realized as graphs of modular services and executed in response to the detection of physical phenomena. We have also implemented a suite of middleware services that support OASiS to provide a layer of abstraction shielding the low-level system complexities. A tracking application is used to illustrate the features of OASiS. Our results demonstrate the feasibility and the benefits of a service-oriented programming framework for composing and deploying applications in resource-constrained sensor networks.

Mobile sensor localization and navigation using RF doppler shifts

Many wireless sensor network applications require knowledge of node placement in order to make sense of sensor data in a spatial context. Networks of mobile sensors require position updates for navigation through the sensing region. The global positioning system is able to provide localization information, however in many situations it cannot be relied on, and alternative localization methods are required. We propose a technique for the localization and navigation of a mobile robot that uses the Doppler-shift in frequency observed by stationary sensor nodes. Our experimental results show that, by using observed RF Doppler shifts, a robot is able to navigate through a sensing region with an average localization error of 1.68 meters.

RF doppler shift-based mobile sensor tracking and navigation

Mobile wireless sensors require position updates for tracking and navigation. We present a localization technique that uses the Doppler shift in radio transmission frequency observed by stationary sensors. We consider two scenarios. In the first, the mobile node is carried by a person. In the second, the mobile node controls a robot. In both approaches the mobile node transmits an RF signal, and infrastructure nodes measure the Doppler-shifted frequency. Such measurements enable us to calculate the position and velocity of the mobile transmitter. Our experimental results demonstrate that this technique is viable and accurate for resource-constrained mobile sensor tracking and navigation.

Radio interferometric angle of arrival estimation

Several localization algorithms exist for wireless sensor networks that use angle of arrival measurements to estimate node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a radio interferometric technique for determining bearings from an anchor node to any number of target nodes at unknown positions. The underlying idea is to group three of the four nodes that participate in a typical radio interferometric measurement together to form an antenna array. Two of the nodes transmit pure sinusoids at close frequencies that interfere to generate a low-frequency beat signal. The phase difference of the measured signal between the third array node and the target node constrains the position of the latter to a hyperbola. The bearing of the node can be estimated by the asymptote of the hyperbola. The bearing estimation is carried out by the node itself, hence the method is distributed, scalable and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearings with an accuracy of approximately 3° in 0.5 sec.

RF angle of arrival-based node localisation

Several localisation algorithms exist for wireless sensor networks that use angle of arrival measurements to derive node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a technique for determining node bearings based on radio interferometric angle of arrival measurements from multiple anchor nodes to any number of target nodes at unknown positions. Least squares triangulation is then used to estimate node position. The position estimation is carried out by the node itself, hence the method is distributed, scalable, and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearing with an average accuracy of 3°, and node position with sub-metre accuracy in approximately 1 s.

Target tracking in heterogeneous sensor networks using audio and video sensor fusion

Heterogeneous sensor networks (HSNs) with multiple sensing modalities are gaining popularity in diverse fields. Tracking is an application that can benefit from multiple sensing modalities. If a moving target emits sound then both audio and video sensors can be utilized. These modalities can complement each other in the presence of high background noise that impairs the audio or visual clutter affecting the video. Audio-video tracking can also provide cues for the other modality for actuation. In this paper, we describe an approach for target tracking in urban environments utilizing an HSN of mote class devices equipped with acoustic sensor boards and embedded PCs equipped with web cameras. Our system employs a Markov Chain Monte Carlo Data Association algorithm for tracking vehicles emitting engine noise. Experimental results from a deployment in an urban environment are used to demonstrate our approach.

Efficient Integration of Web Services in Ambient-aware Sensor Network Applications

Sensor webs are heterogeneous collections of sensor devices that collect information and interact with the environment. They consist of wireless sensor networks that are ensembles of small, smart, and cheap sensing and computing devices that permeate the environment as well as high-bandwidth rich sensors such as satellite imaging systems, meteorological stations, air quality stations, and security cameras. Emergency response, homeland security, and many other applications have a very real need to interconnect such diverse networks and access information in real-time. While Internet protocols and Web standards provide well-developed mechanisms for accessing this information, linking such mechanisms with resource-constrained sensor networks is very challenging because of the volatility of the communication links. This paper presents a service-oriented programming model for sensor networks which permits discovery and access of Web services. Sensor network applications are realized as graphs of modular and autonomous services with well-defined interfaces that allow them to be described, published, discovered, and invoked over the network providing a convenient way for integrating services from heterogeneous sensor systems. Our approach provides dynamic discovery, composition, and binding of services based on an efficient localized constraint satisfaction algorithm that can be used for developing ambient-aware applications that adapt to changes in the environment. A tracking application that employs many inexpensive sensor nodes, as well as a Web service, is used to illustrate the approach. Our results demonstrate the feasibility of ambient-aware applications that interconnect wireless sensor networks and Web services.

Multi-Modal Target Tracking Using Heterogeneous Sensor Networks

The paper describes a target tracking system running on a heterogeneous sensor network (HSN) and presents results gathered from a realistic deployment. The system fuses audio direction of arrival data from mote class devices and object detection measurements from embedded PCs equipped with cameras. The acoustic sensor nodes perform beamforming and measure the energy as a function of the angle. The camera nodes detect moving objects and estimate their angle. The sensor detections are sent to a centralized sensor fusion node via a combination of two wireless networks. The novelty of our system is the unique combination of target tracking methods customized for the application at hand and their implementation on an actual HSN platform.

Time Synchronization in Heterogeneous Sensor Networks

Time synchronization is a critical component in many wireless sensor network applications. Although several synchronization protocols have recently been developed, they tend to break down when implemented on networks of heterogeneous devices consisting of different hardware components and operating systems, and communicate over different network media. In this paper, we present a methodology for time synchronization in heterogeneous sensor networks (HSNs). This includes synchronization between mote and PC networks, a communication pathway that is often used in sensor networks, but has received little attention with respect to time synchronization. In addition, we evaluate clock skew compensation methods including linear regression, exponential averaging, and phase-locked loops. Our HSN synchronization methodology has been implemented as a network service and tested on an experimental testbed. We show that a 6-hop heterogeneous sensor network can be synchronized with an accuracy on the order of microseconds.