Cooperative Wireless Sensor Network Positioning via Implicit Convex Feasibility

We propose a distributed positioning algorithm to estimate the unknown positions of a number of target nodes, given distance measurements between target nodes and between target nodes and number of reference nodes at known positions. Based on a geometric interpretation, we formulate the positioning problem as an implicit convex feasibility problem in which some of the sets depend on the unknown target positions, and apply a parallel projection onto convex sets approach to estimate the unknown target node positions. The proposed technique is suitable for parallel implementation in which every target node in parallel can update its position and share the estimate of its location with other targets. We mathematically prove convergence of the proposed algorithm. Simulation results reveal enhanced performance for the proposed approach compared to available techniques based on projections, especially for sparse networks

TW-TOA based positioning in the presence of clock imperfections

This manuscript studies the positioning problem based on two-way time-of-arrival (TW-TOA) measurements in semi-asynchronous wireless sensor networks in which the clock of a target node is unsynchronized with the reference time. Since the optimal estimator for this problem involves difficult nonconvex optimization, two suboptimal estimators are proposed based on the squared-range least squares and the least absolute mean of residual errors. We formulated the former approach as an extended general trust region subproblem (EGTR) and propose a simple technique to solve it approximately. The latter approach is formulated as a difference of convex functions programming (DCP), which can be solved using a concave–convex procedure. Simulation results illustrate the high performance of the proposed techniques, especially for the DCP approach

Algorithms and Models for Positioning and Scheduling in Wireless Sensor Networks

This thesis considers two problems related to wirelesssensor networks.The first (and main) considered problem is the inference of sensornode positions based on transmissions of RF signals between sensornodes and/or between sensor nodes and fixed reference nodes. Westudy the Cram\ue9r-Rao lower bound on positioning errors inasynchronous wireless sensor networks, and propose positioningalgorithms tailored for implementation in these types of networks.In addition to positioning algorithms, we also study algorithmsfor the estimation of distance between network transceivers basedon transmitted wide-band RF signals, and consider the interactionbetween the ranging and the positioning algorithm. In thealgorithm design, we aim for low complexity and robustness againstthe most common types of error sources, including errors caused byblocked (non-line-of-sight) RF channels, and/or multipathpropagation. On a side-track, we study the feasibility ofcharacterizing the surrounding environment in which a wide-bandwireless sensor network is deployed. This characterization is donein terms of the approximate location of reflective objects thatgenerate significant multi-path components and/oramplify-and-forward relays.The second problem we consider is a scheduling problem thatappears not only in wireless sensor networks, but also in otherwireless networks. We propose a relatively simple model forpacket-loss in a Rayleigh fading environment, and use this modelin an attempt to schedule transmissions in the network so as tominimize the average probability of packet-loss. Since wirelesssensor nodes often only have a limited energy source, and packetretransmissions consume energy, this problem is especiallyimportant in the context of wireless sensor networks

Algorithms and Models for Positioning and Scheduling in Wireless Sensor Networks

This thesis considers two problems related to wirelesssensor networks.The first (and main) considered problem is the inference of sensornode positions based on transmissions of RF signals between sensornodes and/or between sensor nodes and fixed reference nodes. Westudy the Cram\ue9r-Rao lower bound on positioning errors inasynchronous wireless sensor networks, and propose positioningalgorithms tailored for implementation in these types of networks.In addition to positioning algorithms, we also study algorithmsfor the estimation of distance between network transceivers basedon transmitted wide-band RF signals, and consider the interactionbetween the ranging and the positioning algorithm. In thealgorithm design, we aim for low complexity and robustness againstthe most common types of error sources, including errors caused byblocked (non-line-of-sight) RF channels, and/or multipathpropagation. On a side-track, we study the feasibility ofcharacterizing the surrounding environment in which a wide-bandwireless sensor network is deployed. This characterization is donein terms of the approximate location of reflective objects thatgenerate significant multi-path components and/oramplify-and-forward relays.The second problem we consider is a scheduling problem thatappears not only in wireless sensor networks, but also in otherwireless networks. We propose a relatively simple model forpacket-loss in a Rayleigh fading environment, and use this modelin an attempt to schedule transmissions in the network so as tominimize the average probability of packet-loss. Since wirelesssensor nodes often only have a limited energy source, and packetretransmissions consume energy, this problem is especiallyimportant in the context of wireless sensor networks