A Low-Complexity Geometric Bilateration Method for Localization in Wireless Sensor Networks and Its Comparison with Least-Squares Methods

This research presents a distributed and formula-based bilateration algorithm that can be used to provide initial set of locations. In this scheme each node uses distance estimates to anchors to solve a set of circle-circle intersection (CCI) problems, solved through a purely geometric formulation. The resulting CCIs are processed to pick those that cluster together and then take the average to produce an initial node location. The algorithm is compared in terms of accuracy and computational complexity with a Least-Squares localization algorithm, based on the Levenberg–Marquardt methodology. Results in accuracy vs. computational performance show that the bilateration algorithm is competitive compared with well known optimized localization algorithms

Comparative node selection-based localization technique for wireless sensor networks: A bilateration approach

Wireless sensor networks find extensive applications, such as environmental and smart city monitoring, structural health, and target location. To be useful, most sensor data must be localized. We propose a node localization technique based on bilateration comparison (BACL) for dense networks, which considers two reference nodes to determine the unknown position of a third node. The mirror positions resulted from bilateration are resolved by comparing their coordinates with the coordinates of the reference nodes. Additionally, we use network clustering to further refine the location of the nodes. We show that BACL has several advantages over Energy Aware Co-operative Localization (EACL) and Underwater Recursive Position Estimation (URPE): (1) BACL uses bilateration (needs only two reference nodes) instead of trilateration (that needs three reference nodes), (2) BACL needs reference (anchor) nodes only on the field periphery, and (3) BACL needs substantially less communication and computation. Through simulation, we show that BACL localization accuracy, as root mean square error, improves by 53% that of URPE and by 40% that of EACL. We also explore the BACL localization error when the anchor nodes are placed on one or multiple sides of a rectangular field, as a trade-off between localization accuracy and network deployment effort. Best accuracy is achieved using anchors on all field sides, but we show that localization refinement using node clustering and anchor nodes only on one side of the field has comparable localization accuracy with anchor nodes on two sides but without clustering

A Localization Method Avoiding Flip Ambiguities for micro-UAVs with Bounded Distance Measurement Errors

Localization is a fundamental function in cooperative control of micro unmanned aerial vehicles (UAVs), but is easily affected by flip ambiguities because of measurement errors and flying motions. This study proposes a localization method that can avoid the occurrence of flip ambiguities in bounded distance measurement errors and constrained flying motions; to demonstrate its efficacy, the method is implemented on bilateration and trilateration. For bilateration, an improved bi-boundary model based on the unit disk graph model is created to compensate for the shortage of distance constraints, and two boundaries are estimated as the communication range constraint. The characteristic of the intersections of the communication range and distance constraints is studied to present a unique localization criterion which can avoid the occurrence of flip ambiguities. Similarly, for trilateration, another unique localization criterion for avoiding flip ambiguities is proposed according to the characteristic of the intersections of three distance constraints. The theoretical proof shows that these proposed criteria are correct. A localization algorithm is constructed based on these two criteria. The algorithm is validated using simulations for different scenarios and parameters, and the proposed method is shown to provide excellent localization performance in terms of average estimated error. Our code can be found at: https://github.com/QingbeiGuo/AFALA.git.Comment: 14 pages, 8 figures, IEEE Transactions on Mobile Computing(Accepted

A New Approach towards Solving the Location Discovery Problem in Wireless Sensor Networks

Location discovery in wireless sensor network (WSN) is the process that sensor nodes collaborate to determine the position for unknown sensor nodes. Anchors, sensors that know their locations, are expensive but are required to be deployed into the WSN to solve this problem. Thus it is desirable to minimize the number of anchors for this purpose. In this paper, we propose an anchor deployment scheme and a novel bilateration locationing algorithm to achieve this goal. The basic idea of anchor deployment method is to have three anchors deployed as a group, and locate sensors around them expansively. The novelty of our bilateration algorithm is that it in general requires only two neighbor sensors to determine a node's location. Comparing with the state-of-the-art location discovery approaches, our algorithm gives location estimation with high accuracy, low communication cost and very small anchor percentage. We conduct theoretical analysis about location estimation error and extensive simulation shows that our algorithm can derive sensor location within 4% location error and much less communication cost compared with other algorithms. UMIACS-TR-2003-11

Enhanced Performance Cooperative Localization Wireless Sensor Networks Based on Received-Signal-Strength Method and ACLM

There has been a rise in research interest in wireless sensor networks (WSNs) due to the potential for his or her widespread use in many various areas like home automation, security, environmental monitoring, and lots more. Wireless sensor network (WSN) localization is a very important and fundamental problem that has received a great deal of attention from the WSN research community. Determining the relative coordinate of sensor nodes within the network adds way more aiming to sense data. The research community is extremely rich in proposals to deal with this challenge in WSN. This paper explores the varied techniques proposed to deal with the acquisition of location information in WSN. In the study of the research paper finding the performance in WSN and those techniques supported the energy consumption in mobile nodes in WSN, needed to implement the technique and localization accuracy (error rate) and discuss some open issues for future research. The thought behind Internet of things is that the interconnection of the Internet-enabled things or devices to every other and human to realize some common goals. WSN localization is a lively research area with tons of proposals in terms of algorithms and techniques. Centralized localization techniques estimate every sensor node's situation on a network from a central Base Station, finding absolute or relative coordinates (positioning) with or without a reference node, usually called the anchor (beacon) node. Our proposed method minimization error rate and finding the absolute position of nodes

Design and realization of precise indoor localization mechanism for Wi-Fi devices

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.Peer ReviewedPostprint (published version

Range-free selective anchor node center of the smallest communication overlap polygon localization algorithm in wireless networks

International audienceThis paper presents a range-free selective anchor node center of the smallest communication overlap polygon localization algorithm in wireless networks. The algorithm is range-free which does not require ranging devices. To estimate the location of unknown (location unaware) nodes it uses node connectivity based on selected anchor (location aware) nodes. The algorithm first selects appropriate anchor nodes. Then, the True Intersection Points (TIPs) constituting the vertices of the smallest communication overlap polygon (SCOP) of these selected anchor nodes' communication ranges are found. Finally, the location of the unknown node is estimated at the center of the SCOP which is formed from these TIPs. The algorithm performance is evaluated using MatLab simulation and compares favorably to state-of-the-art algorithms: Centroid, improved version of CPE, Mid-perpendicular and CSCOP localization algorithms. The results show the proposed algorithm outperforms other state-of-the-art algorithms in location accuracy and it has reasonable computational complexity

Joint position estimation, packet routing and sleep scheduling in wireless sensor networks

Wireless Sensor Network (WSN) is an important research field in Computer Science with applications that span multiple domains. Due to the limitation of sensor nodes, network lifetime is a critical issue that needs to be addressed. Therefore, in this thesis I propose the Energy-aware Connected k-Neighbourhood (ECKN), a joint position estimation, packet routing, and sleep scheduling solution that combines some overlap- ping features. I propose a localization algorithm that performs trilateration using the position of a mobile sink and of neighbour nodes to estimate the position of a sensor node with no GPS module. I introduce a routing protocol based on the well-known Greedy Geographic Forwarding (GGF). Similarly to GGF, my protocol takes into consideration the position of neighbours to decide the best forwarding node, however it also considers the residual energy in order to guarantee that the forwarding node will deliver the packet. The concept of bridges is also introduced, in which the sink compares its current position with previous positions and calculates whether there is a shortest path in order to create a bridge that will reduce the number of hops a packet has to travel through. Lastly, a sleep scheduler is proposed in order to extend the network lifetime, it is based on the Connected k-Neighbourhood (CKN) algorithm, which aids in the decision of what nodes goes to sleep while maintaining the network connected. My sleep scheduler maintains the network denser in the area close to the sink, since this region receives packets from the whole network to forward to the sink. An extensive set of performance evaluation experiments is conducted and results show that ECKN can extend network lifetime, while sustaining acceptable packet delivery ratio and reducing network overhead

Neighbor Constraint Assisted Distributed Localization for Wireless Sensor Networks

Localization is one of the most significant technologies in wireless sensor networks (WSNs) since it plays a critical role in many applications. The main idea in most localization methods is to estimate the sensor-anchor distances that are used by sensors to locate themselves. However, the distance information is always imprecise due to the measurement or estimation errors. In this work, a novel algorithm called neighbor constraint assisted distributed localization (NCA-DL) is proposed, which introduces the application of geometric constraints to these distances within the algorithm. For example, in the case presented here, the assistance provided by a neighbor will consist in formulating a linear equality constraint. These constraints can be further used to formulate optimization problems for distance estimation. Then through some optimization methods, the imprecise distances can be refined and the localization precision is improved

Novel range-free immune to radio range difference (IRRD) geo-localization algorithm in wireless networks

This paper presents a novel range-free immune to radio range difference (IRRD) geo-localization algorithm in wireless networks. The algorithm does not require the traditional assumption of anchor (location aware) nodes that have the same communication range as it works with anchor nodes having homogeneous and/or heterogeneous communication ranges. It is rang-free - it utilizes node connectivity to estimate the position of unknown (location unaware) nodes using two or more anchor nodes. The algorithm works in two steps: in the first step, the True Intersection Points (TIPs) forming the vertices of the smallest communication overlap polygon (SCOP) of the anchor nodes are found. In the second step, it estimates the position of the unknown node at the center of the SCOP which is formed from these TIPs. The problem is first geometrically and mathematically modeled, then new localization approach that does not assume anchor nodes have the same radio range is proposed