3 research outputs found
Wireless distance estimation with low-power standard components in wireless sensor nodes
In the context of increasing use of moving wireless sensor nodes the interest
in localizing these nodes in their application environment is strongly rising.
For many applications, it is necessary to know the exact position of the nodes
in two- or three-dimensional space. Commonly used nodes use state-of-the-art
transceivers like the CC430 from Texas Instruments with integrated signal
strength measurement for this purpose. This has the disadvantage, that the
signal strength measurement is strongly dependent on the orientation of the
node through the antennas inhomogeneous radiation pattern as well as it has a
small accuracy on long ranges. Also, the nodes overall attenuation and output
power has to be calibrated and interference and multipath effects appear in
closed environments. Another possibility to trilaterate the position of a
sensor node is the time of flight measurement. This has the advantage, that the
position can also be estimated on long ranges, where signal strength methods
give only poor accuracy. In this paper we present an investigation of the
suitability of the state-of-the-art transceiver CC430 for a system based on
time of flight methods and give an overview of the optimal settings under
various circumstances for the in-field application. For this investigation, the
systematic and statistical errors in the time of flight measurements with the
CC430 have been investigated under a multitude of parameters. Our basic system
does not use any additional components but only the given standard hardware,
which can be found on the Texas Instruments evaluation board for a CC430. Thus,
it can be implemented on already existent sensor node networks by a simple
software upgrade.Comment: 8 pages, Proceedings of the 14th Mechatronics Forum International
Conference, Mechatronics 201
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