The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Position calibration of audio sensors and actuators in a distributed computing platform
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Semidefinite programming for ad hoc wireless sensor network localization
Proceedings of the 3rd international symposium on Information processing in sensor networks
New direct approaches to robust sound source localization
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
IEEE Transactions on Signal Processing
Accurate GSM indoor localization
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
IEEE Transactions on Signal Processing
IEEE Communications Magazine
Hi-index | 5.23 |
We present an approach for the localization of passive nodes in a communication network using ambient radio or sound signals. In our settings, the communication nodes have unknown positions. They do not emit signals for localization and exchange only the time points when environmental signals are received: the time differences of arrival (TDOA). The signals occur at distant but unknown positions and they can be distinguished. Since no anchors are available, the goal is to determine the relative positions of all communication nodes and the environmental signals. Our novel approach, the Ellipsoid TDOA method, introduces a closed form solution assuming that the signals originate from remote distances. The TDOA measurements characterize an ellipse from which the distances and angles between three network nodes can be inferred. In contrast to existing approaches, we do not require the receiver nodes to be synchronized. Furthermore, we can calculate the time offsets of the receiver clocks as a result of our calculations and synchronize the receivers in this way. The approach is tested in numerous simulations and in indoor and outdoor settings, where the relative positions of mobile devices are determined using only the sounds produced by assistants with noisemakers.