15,394 research outputs found
Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks
Accurate localization for mobile nodes has been an important and fundamental
problem in underwater acoustic sensor networks (UASNs). The detection
information returned from a mobile node is meaningful only if its location is
known. In this paper, we propose two localization algorithms based on color
filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively
accomplishing accurate localization of underwater mobile nodes with minimum
energy expenditure. They both adopt the overlapping signal region of task
anchors which can communicate with the mobile node directly as the current
sampling area. PCFL employs the projected distances between each of the task
projections and the mobile node, while ACFL adopts the direct distance between
each of the task anchors and the mobile node. Also the proportion factor of
distance is proposed to weight the RGB values. By comparing the nearness
degrees of the RGB sequences between the samples and the mobile node, samples
can be filtered out. And the normalized nearness degrees are considered as the
weighted standards to calculate coordinates of the mobile nodes. The simulation
results show that the proposed methods have excellent localization performance
and can timely localize the mobile node. The average localization error of PCFL
can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table
Localisation of mobile nodes in wireless networks with correlated in time measurement noise.
Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in time measurement noises. Two approaches to deal with the correlated measurement noises are proposed in the framework of auxiliary particle filtering: with a noise augmented state vector and the second approach implements noise decorrelation. The performance of the two proposed multi model auxiliary particle filters (MM AUX-PFs) is validated over simulated and real RSSIs and high localisation accuracy is demonstrated
Locating sensors with fuzzy logic algorithms
In a system formed by hundreds of sensors deployed
in a huge area it is important to know the position where every
sensor is.
This information can be obtained using several methods.
However, if the number of sensors is high and the deployment
is based on ad-hoc manner, some auto-locating techniques must
be implemented.
In this paper we describe a novel algorithm based on fuzzy
logic with the objective of estimating the location of sensors
according to the knowledge of the position of some reference
nodes.
This algorithm, called LIS (Localization based on Intelligent
Sensors) is executed distributively along a wireless sensor network
formed by hundreds of nodes, covering a huge area.
The evaluation of LIS is led by simulation tests. The result
obtained shows that LIS is a promising method that can easily
solve the problem of knowing where the sensors are located.Junta de Andalucía P07-TIC-0247
A survey of localization in wireless sensor network
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
Reference Nodes Selection for Anchor-Free Localization in Wireless Sensor Networks
Dizertační práce se zabývá návrhem nového bezkotevního lokalizačního algoritmu sloužícího pro výpočet pozice uzlů v bezdrátových senzorových sítích. Provedené studie ukázaly, že dosavadní bezkotevní lokalizační algoritmy, pracující v paralelním režimu, dosahují malých lokalizačních chyb. Jejich nevýhodou ovšem je, že při sestavení množiny referenčních uzlu spotřebovávají daleko větší množství energie než algoritmy pracující v inkrementálním režimu. Paralelní lokalizační algoritmy využívají pro určení pozice referenční uzly nacházející se na protilehlých hranách bezdrátové sítě. Nový lokalizační algoritmus označený jako BRL (Boundary Recognition aided Localization) je založen na myšlence decentralizovaně detekovat uzly ležící na hranici síti a pouze z této množiny vybrat potřebný počet referenčních uzlu. Pomocí navrženého přístupu lze znažně snížit množství energie spotřebované v průběhu procesu výběru referenčních uzlů v senzorovém poli. Dalším přínosem ke snížení energetických nároku a zároveň zachování nízké lokalizační chyby je využití procesu multilaterace se třemi, eventuálně čtyřmi referenčními body. V rámci práce byly provedeny simulace několika dílčích algoritmu a jejich funkčnost byla ověřena experimentálně v reálné senzorové síti. Navržený algoritmus BRL byl porovnán z hlediska lokalizační chyby a počtu zpracovaných paketů s několika známými lokalizačními algoritmy. Výsledky simulací dokázaly, že navržený algoritmus představuje efektivní řešení pro přesnou a zároveň nízkoenergetickou lokalizaci uzlů v bezdrátových senzorových sítích.The doctoral thesis is focused on a design of a novel anchor free localization algorithm for wireless sensor networks. As introduction, the incremental and concurrent anchor free localization algorithms are presented and their performance is compared. It was found that contemporary anchor free localization algorithms working in the concurrent manner achieve a low localization error, but dissipate signicant energy reserves. A new Boundary Recognition Aided Localization algorithm presented in this thesis is based on an idea to recognize the nodes placed on the boundary of network and thus reduce the number of transmission realized during the reference nodes selection phase of the algorithm. For the position estimation, the algorithm employs the multilateration technique that work eectively with the low number of the reference nodes. Proposed algorithms are tested through the simulations and validated by the real experiment with the wireless sensor network. The novel Boundary Recognition Aided Localization algorithm is compared with the known algorithms in terms of localization error and the communication cost. The results show that the novel algorithm presents powerful solution for the anchor free localization.
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