Design and analysis of distance error correction–based localization algorithm for wireless sensor networks

Abstract

Localization error is the main criteria to decide the efficiency on any localization approach. In case of range‐free hop‐based localization approaches, position coordinates estimation is done through the common steps like the calculation of the minimum hop count, hop size, and then later on applying the multilateration or least square approach. There are many improvements that have been made in the form of various algorithms through some changes in the common steps for the reduction of localization error. It has been observed that the existing algorithms are still having the highest value of localization error. To overcome the deficiencies in the existing algorithms, a novel distance error correction metric–based approach has been introduced. This paper presents a distance error correction–based algorithm (DEC‐hop) for the hop‐based localization approach for a wireless sensor network. Distance‐based error correction factor that is introduced in this paper further reduces the localization error value to some extent. For measuring the effectiveness and the preciseness of the given approach, it is inspected with other improved algorithms based on DV‐hop. Simulation results have confirmed that the proposed error correction–based algorithm outperforms the other variety of improved hop‐based algorithms. Results are analyzed in terms of various factors like the localization error, accuracy, and error variance against the parameters of interest taken as node amount, anchor ratio, and communication range of the node.

Research on application of dynamic threshold least squares Beidou positioning algorithm in Beidou geological disaster monitoring in Three Gorges Reservoir Area

“…The calculation process of the least squares algorithm is a process of iterating from the initial value, so it is necessary to set the initial value in the first linearization of the equation. The satellite receiver's position ( x , y , z ) and the satellite receiver's clock error δt u can be obtained by using the pseudo‐range equation 15 . In this case, it is necessary to set the initial value ( x 0 , y 0 , z 0 ) and δt u, 0 for the satellite receiver's position and clock error.…”

“…The satellite receiver's position (x, y, z) and the satellite receiver's clock error t u can be obtained by using the pseudo-range equation. 15 In this case, it is necessary to set the initial value (x 0 , y 0 , z 0 ) and t u, 0 for the satellite receiver's position and clock error. During the continuous use of the satellite receiver, if the satellite receiver has been successfully positioned at the previous moment, the position of the receiver and the satellite clock error can be solved as the initial iteration value of the position and clock error of the satellite F I G U R E 1 Observation vector of the receiver pointing to the satellite receiver in the quaternary nonlinear equations in the next moment.…”

SDSWSN—A Secure Approach for a Hop-Based Localization Algorithm Using a Digital Signature in the Wireless Sensor Network

“…In this part of the paper, two schemes are defined: one is the proposed secure approach based on the authentication of nodes using digital signatures; the other is the improved DV-Hop approach based on a distance error correction factor using the hyperbolic function [47,48]. Most importantly, the localization involves two kinds of nodes.…”

Analysis of security and energy efficiency for shortest route discovery in low‐energy adaptive clustering hierarchy protocol using Levenberg‐Marquardt neural network and gated recurrent unit for intrusion detection system

“…This leads to prolonging the battery life of each nodes. 24,25 Therefore, to further improve the overall network lifetime, after completion of data aggregation phase in each cluster. The aggregated data at each CH node are transmitted to base station via intermediate nodes.…”