Virtual Anchors Research Articles

An Event-Driven Object Localization Method Assisted by Beacon Mobility and Directional Antennas

An event-driven object localization method based on directional antennas is proposed in this paper. First the event occurrence spot is divided into four sections. Then low altitude UAV (Unmanned Aerial Vehicle) is employed to deploy DAWSN (Wireless Sensor Networks for Disaster Assistance) for urgent observation and communication. By means of a mobile anchor with four directional antennas and a GPS module, obstacle avoidance traverse in DAWSN is realized and the locations during mobility are broadcast. Unknown nodes take these locations as virtual anchors and project them onto a virtual motion path, and then the coordinates of unknown nodes are solved with extended directional localization method. This range-free method does not require plenty of anchor nodes and complicated computation. With small positioning error and large positionable node ratio (PNR), it allows the virtual anchor to move along any curve path and can be utilized under the event-driven scenario to provide self-localization for DAWSN.

Convex Combination Based Target Localization with Noisy Angle of Arrival Measurements

Target localization based on angle of arrival (AoA) is an important branch of location estimation research. Due to the noisy measurements from sensors and the non-linear inverse trigonometry function, the AoA-based localization induces a non-convex optimization that is difficult to solve with both high speed and accuracy simultaneously. To achieve a fast and accurate algorithm, we propose a convex combination scheme. By introducing a highly accurate linear approximation to the inverse trigonometric function, the objective is converted to a convex function, which can be solved efficiently with linear least-squares approach. The key point of the convex combination scheme is to express the coordinate of the target as the convex combination of a set of virtual anchors around its real position. Simulations demonstrate that the accuracy of this method is very close to the Cramer-Rao lower bound and that the comprehensive performance, including the accuracy and speed, is significantly improved compared to other state-of-the-art methods.

A linear combination-based weighted least square approach for target localization with noisy range measurements

Target localization based on range measurements from a set of anchors plays an important role in positioning systems and sensor networks. The localization is generally formulated as an optimization problem to tackle the noisy measurements. However, the objective is non-convex, and thus localization is difficult to solve in its original form. In this paper, a convex objective function is derived based on a linear combination scheme, within which the target position is expressed as a linear combination of positions of virtual anchors around its real position. In addition, the linear combination provides a highly accurate approximation for the computation of the distance from the anchors. Thus, the localization is formulated as a convex problem to find the optimal coefficients of the linear combination and is solved efficiently by the weighted linear least square method. As demonstrated by numerical experiments, the proposed approach, which achieves an approximately 35% improvement in accuracy and 98.5% shorter optimization time compared to the most accurate existing method, is very close to the Cramér–Rao lower bound (CRLB) while maintaining a quite high localization speed, and also works well with real measurement data.

RSSI WSN localization with Analysis of Energy Consumption and Communication

Distance based localization techniques have always been of interest among researchers. The free received signal strength index (RSSI) requires no extra hardware for distance measurement. Authors in this paper assume that RSSI based distance estimation technique will have some error due to noisy RSSI readings. The localization algorithm proposed here takes into account this error and localizes a WSN in three stages. Due to this error in distance, nodes in neighbor of three anchor nodes determine their uncertainty region with some accuracy and become virtual anchors. These nodes then help other nodes in the network to determine their region. These non virtual anchor nodes collaborate among themselves to further decrease the size of uncertainty region. The collaborative nature of nodes is exploited to increase the accuracy and precision of localization. The authors in this paper have used only three anchor nodes to localize a full blown Wireless Sensor Network (WSN) of 100 nodes with better accuracy compared to existing techniques using RSSI till date. Authors also analyze the energy and communication cost involved in localization process.

Energy-efficient geographic routing with virtual anchors based on projection distance

Geographic routing is an effective routing technique based on locally available position information. It uses greedy forwarding whenever possible and switches to detouring mode when a local minimum is reached. Detouring mode in geographic routing usually results in lengthy paths. To shorten the path and reduce the possibility of detouring, geographic routing using anchor nodes as intermediate relays has been proposed. In this paper, we propose to obtain the anchor list based on the projection distance of nodes in detouring mode with respect to the virtual line linking the source and destination. For existing anchor-based schemes, once an anchor list is obtained, the path from the source to the destination usually does not change unless the network topology changes, which may lead to the quick depletion of the energy for some nodes. To better distribute energy consumption among nodes in the network and thus prolong the network lifetime, we further propose to introduce a random shift to the location of anchors to obtain virtual anchors for each packet sent. Simulation results show that our projection distance-based algorithm outperforms existing anchor-based algorithms with shorter paths and fewer anchors in random network topology. We also demonstrate that the lifetime-improving strategy with virtual anchors is effective in increasing the number of packets delivered in the lifetime of sensor networks.