Design of a wireless sensor network platform for detecting rare, random, and ephemeral events

Sallai

Lecture Notes in Computer Science

et al. 2010

Abstract. 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.

“…Our system is implemented using Crossbow ExScal motes (XSMs) [21], which use the Texas Instruments CC1000 radio chip and transmit in the 433 MHz range. Three XSMs form the array.…”

Section: Methodsmentioning

confidence: 99%

Radio Interferometric Angle of Arrival Estimation

Sallai

Lecture Notes in Computer Science

et al. 2010

“…Mobile embedded nodes do not control their own movement; rather, their motion is directed by some external force, such as when tethered to an animal [8] or attached to a shipping container [9]. Typical embedded sensors include [10], [11], and [12].…”

Section: Mwsn Architecturesmentioning

confidence: 99%

A Survey on Localization for Mobile Wireless Sensor Networks

Lecture Notes in Computer Science

2009

255

142

Abstract. 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.

“…VI. IMPLEMENTATION Our mobile sensor is comprised of an XSM mote [12] attached to an iRobot Create mobile platform [13], as pictured in Figure 10. All localization and control operations are performed on the mote, which communicates with the Create microcontroller over a serial interface.…”

Section: Latencymentioning

confidence: 99%

Mobile Sensor Navigation Using Rapid RF-Based Angle of Arrival Localization

2011 17th IEEE Real-Time and Embedded Technology and Applications Symposium

Sallai

et al. 2011

Abstract-Over the past decade, wireless sensor networks have advanced in terms of hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been growing interest in mobile wireless sensor networks, and several small-profile sensing devices that are able to control their own movement have already been developed. Unfortunately, resource constraints inhibit the use of traditional navigation methods, because these typically require bulky, expensive, and sophisticated sensors, substantial memory and processor allocation, and a generous power supply. Therefore, alternative navigation techniques are required. In this paper we present TripNav, a localization and navigation system that is implemented entirely on resource-constrained wireless sensor nodes. Localization is realized using radio interferometric angle of arrival estimation, in which bearings to a mobile node from a small number of infrastructure nodes are estimated based on the observed phase differences of an RF interference signal. The position of the mobile node is then determined using triangulation. A digital compass is also employed to keep the mobile node from deviating from the desired trajectory. We demonstrate using a real-world implementation that a resource-constrained mobile sensor node can accurately perform waypoint navigation with an average position error of 0.95 m.