Conference Paper

Nodes localization through data fusion in sensor network

Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi, Taiwan
DOI: 10.1109/AINA.2005.259 Conference: Advanced Information Networking and Applications, 2005. AINA 2005. 19th International Conference on, Volume: 1
Source: IEEE Xplore


The location of nodes in sensor network is an important problem with application in resource allocation, location sensitive browsing, and emergency communications. A key problem in sensor network location is the creation of a method that is robust to measurement quantization and measurement noise and also has a reasonable implementation cost. The RSS and TDoA are the popular distance measurement methods, but can be easy affected by noise and not independent. This paper explores a covariance intersection (CI) that fuses together location estimations obtained from power propagation loss measurements and propagation time to obtain higher accuracy location estimate. The performances of Kalman filter type estimators are severely affected by the ignored cross covariance. CI algorithm provides a mechanism to fuse two or more random variables with unknown correlation such that the computed covariance of the new estimate is consistent; therefore CI method is quite suitable for sensor network application. In simulation result shows that position estimates are correct within small ranging distance with few initial master nodes of the system.

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    • "Now, it's time to examine the second problem, i.e. the error Figure 1. First Rule, x is a node looking for its position [6] Figure 2. Second Rule [6] Figure 3. Third Rule [7] accumulation and its solution. We solve the abovementioned problem by clustering. "
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    ABSTRACT: the determination of sensor node's position is one of the important issues in sensor networks. Several methods have been presented in order to determine the position of nodes in these networks. Among them, the "Data Fusion" method, due to the combinational utilization of TDOA and RSS has been able to calculate the distance between nodes more accurately. In the method presented in this paper, by using a series of rules, clustering and Prioritizing in choosing reference nodes the precision of localization of "Data Fusion" Method has been increased, particularly in those locations where the density of reference nodes is little in the network or those places in which the network has holes. Meanwhile, we were able to avoid Error dissemination in network, by applying clustering. The simulation results show that, in a similar environment, the suggested method is more accurate comparing to the existing localization methods. It also has appropriate reliability as well.
    Full-text · Conference Paper · Jan 2011
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    • "Some algorithms assume that the relative distances are known in advance [8] and the others propose approaches to distance measurement. Distances can be measured by measuring the power of the signal at the receiver (RSSI), Time of Arrival (ToA) for electrical [9], and ultrasonic signals [10]. But these methods require each sensor node being equipped with CPU and powerful computation capability. "
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    ABSTRACT: Localization by connectivity in wireless sensor networks is an approach that does not impose any additional hardware to sensor nodes and it only uses connectivity information. In this approach localization is erroneous. In this paper we propose a formula to estimate average of error in localization of random sensor network. The work is started with a view on localization in regular distributed network. Obtained formula will be generalized for randomly distributed network using the random density function of connectivity. Proposed formula shows that the error rate is different depending on the network parameters. Simulation results confirm the performance and correctness of the formula.
    Full-text · Conference Paper · Nov 2008
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    • "This paper focuses on how to solve the problem of full coverage and connection encountered in wireless sensor networks. Initially, we use the concept of virtual grids for effective full area coverage and connection [2] [4] [5] [6] [7] [8] [9]. Subsequently, we propose the CLD (controlled layer deployment) as a sensor node deployment protocol in order to prolong the lifetime of the whole network, and resolve the above-mentioned problems. "
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    ABSTRACT: In many scenarios, sensor nodes have to rely on a limited supply of energy (using batteries). To support long lifetime of wireless sensor networks (WSN), an energy-efficient way of operation of the WSN is necessary. In this paper, we propose a new controlled layer deployment (CLD) routing protocol to guarantee coverage and energy efficiency on a sensor network. CLD outperforms PEAS (probing environment and adaptive sleeping) and the TTDD (two-tier data dissemination) protocols in that it can guarantee full area coverage and connection. It can also solve the "cascading problem" which reduces the whole network lifetime. Finally, we show the results of the simulation to prove that the new protocol can use fewer sensor nodes for coverage and increase the lifetime as compared to the PEAS protocol.
    Full-text · Conference Paper · Apr 2007
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