A three-dimensional node localization algorithm of high-precision in wireless sensor network

The localization technique is an important requirement in wireless sensor networks (WSNs). Many localization algorithms in WSNS have been proposed. This paper presents a novel three-dimensional localization algorithms LIE-3D in WSNs. This approach is about that the target sensor performed LIE-3D test to judge the grid of the vote, which narrowed down the possible location areas, and finally calculate the intersection of these areas part of the mass center, as the location of the node to be positioning. As a result, theoretical analysis and experimental results show that LIE-3 D depends on no ranging measures or global infrastructure, it presents a low-cost solution for self-localization of densely deployed and large scale WSNs in 3D spaces.Keywordswireless sensor networksThree-dimensional localizationLocalization accuracygrid

In wireless sensor network, determine the position of the node position or events is very important to its surveillance activities, however, in the traditional wireless sensor network, are using two-dimensional spatial positioning technology, aiming at this problem, this article will wireless sensor network (WSN) 2 d algorithm is extended to 3 d space, analyzes the main factors affecting the positioning accuracy of wireless sensor network. In order to further improve the stability and precision of the algorithm, by introducing the Newton's method, gives the quasi-newton three-dimensional node localization hybrid localization algorithm. The simulation analysis shows that the proposed hybrid algorithm can under the same conditions with high positioning accuracy and stability, at the same time the CRLB are obtained. The simulation results show that the proposed algorithm can get g Latin American community, simulation analysis of the localization method is effective

Bistatic multiple-input multiple output (MIMO) radar can achieve target localization by estimating the transmit and receive angles. In this paper, an ESPRIT based threedimensional (3-D) localization algorithm is proposed for bistatic MIMO radar system with a uniform circular array on transmit and a uniform linear array on receive. Transmit azimuth, transmit elevation angles and receive cone angle are estimated by using the receive data. The 3-D coordinates of the target are then calculated by using the geometry between targets and radar. The accuracy of target localization is independent of the signal bandwidth as the range of the target is not required. Also the time synchronization is avoided in process of the target localization. Simulations demonstrate the effectiveness of the proposed method. (4 pages)

The wireless sensor network node localization algorithms are studied more and more at present, but most are based on two-dimensional localization algorithm for three-dimensional localization of too few. Based on the researches on the classic two-dimensional localization algorithm, and the trilateration was extended to three-dimensional localization algorithm. Error analysis of this algorithm was revealed in the classic two-dimensional and three-dimensional environment, and the node localization error with a linear relationship between average nodes ranging error was found.

Location information is generally considered to be indispensable information in wireless sensor networks, but existing algorithms have notable limitations in their positioning accuracy in 3-dimensional (3D) spaces. To improve the positioning accuracy of nodes in a 3D scenario, this paper proposes a new method called N2-3DDV-Hop (non-dominated sorting genetic algorithm II with 3D distance-vector hop) that builds on the 3D-DV-Hop algorithm by adding multi-objective model and NSGA-II. In this paper, it is analyzed that the limitations of the traditional single-objective positioning model and showed the relationship among the average hop distance, the number of sensor nodes, and the theoretical average distance. In addition then, the multi-objective positioning model incorporating the NSGA-II algorithm is presented. To evaluate its performance relative to other current methods, we compared our method by testing all of the methods with three different complex network topologies. Simulation results demonstrate that the N2-3DDV-Hop offered the best overall positioning performance compared with other algorithms and better robustness than the 3DDV-Hop algorithm.

Ultra-wideband (UWB) technology has the characteristics which other wireless communication technology can not match to. It combines with wireless sensor network (WSN) technology, using in the environment of coal mine underground, to achieve safety monitoring by WSN node location. Using appropriate location algorithm can not only improve the location accuracy of the calculation can also reduce system cost and power consumption. This paper mainly describes the basic nodes location principle and algorithm of WSN, proposes the location algorithm which is suitable for coal mine environment, and improves it based on traditional ranging and location method. Simulation results show that the improved location algorithm effectively improves location accuracy and location performance of the node.

We propose a novel low-complexity three-dimensional (3D) localization algorithm for wireless sensor networks, termed quaternion-domain super multidimensional scaling (QD-SMDS). This algorithm reformulates the conventional SMDS, which was originally developed in the real domain, into the quaternion domain. By representing 3D coordinates as quaternions, the method enables the construction of a rank-1 Gram edge kernel (GEK) matrix that integrates both relative distance and angular (phase) information between nodes, maximizing the noise reduction effect achieved through low-rank truncation via singular value decomposition (SVD). The simulation results indicate that the proposed method demonstrates a notable enhancement in localization accuracy relative to the conventional SMDS algorithm, particularly in scenarios characterized by substantial measurement errors.

This paper firstly analyzes and points out the problems of the traditional DV-Hop algorithm, then proposes a node localization algorithm based on the hop distance optimization, which uses the actual path distance between two anchor nodes instead of the traditional linear distance to calculate the average hop distance of anchor nodes, and further calculates the average hop distance of unknown nodes with the help of multiple anchor nodes. The simulation results show that the proposed localization algorithm can effectively improve the localization accuracy of nodes, especially in the 3D outdoor environment without ranging.

Currently, most of node localization algorithms are designed based on the two-dimensional space, but the practical application is carried out in three-dimensional space. A three-dimensional node localization hybrid algorithm called DV-Hop-AC-PSO is proposed, which combines the advantages of DV-Hop, ant colony and particle swarm algorithm. In the proposed algorithm, particle swarm algorithm is adopted to optimize the parameters of the ant colony algorithm, and DV-Hop algorithm is used in the iterative process of ant colony algorithm to improve the localization accuracy. Experimental results prove the effectiveness of the proposed algorithm.

In many wireless sensor network (WSN) applications, the information transmitted by an individual entity or node is of limited use without the knowledge of its location. Research in node localization is mostly geared towards multi-hop range-free localization algorithms to achieve accuracy by minimizing localization errors between the node's actual and estimated position. The existing localization algorithms are focused on improving localization accuracy without considering efficiency in terms of energy costs and algorithm convergence time. In this work, we show that our proposed localization scheme, called DV-maxHop, can achieve good accuracy and efficiency. We formulate the multi-objective optimization functions to minimize localization errors as well as the number of transmission during localization phase. We evaluate the performance of our scheme using extensive simulation on several anisotropic and isotropic topologies. Our scheme can achieve dual objective of accuracy and efficiency for various scenarios. Furthermore, the recently proposed algorithms require random uniform distribution of anchors. We also utilized our proposed scheme to compare and study some practical anchor distribution schemes.

Aiming at localization algorithms in 3D space which has some problems such as high complexity, large power consumption, long delay and so on, a 3D localization algorithm was proposed which combines DV-Hop with cube shell intersection method. This algorithm improves the DV-Hop in a special situation to get the unknown nodes’ initial positions and employs the Cube Radius scale to get the final position. The theoretical analysis shows this algorithm has low complexity. Compared with 3D-DV-Hop, the location accuracy and fraction of coverage of this algorithm were improved obviously.

As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.

This paper conducts research on the algorithm to improve the location of Wireless Sensor Network (WSN) in Intelligent Transportation System (ITS). The localization algorithm introduced an improved RSSI vehicle localization algorithm based on multi-path effect and Gaussian white noise. The localization results under different values of Gaussian white noise and different density of beacon nodes are analyzes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, a simulation model of ITS is developed to test the algorithm based on mixed noise and Kalman filtering algorithm, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application

This paper conducts research on the algorithm to improve the location of Wireless Sensor Network (WSN) in Intelligent Transportation System (ITS). The localization algorithm introduced an improved RSSI vehicle localization algorithm based on multi-path effect and Gaussian white noise. The localization results under different values of Gaussian white noise and different density of beacon nodes are analyzes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, a simulation model of ITS is developed to test the algorithm based on mixed noise and Kalman filtering algorithm, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application

Location information is a fundamental requirement for unmanned aerial vehicles (UAVs) and other wireless sensor networks (WSNs). However, accurately localizing sensor nodes with diverse functionalities remains a significant challenge, particularly in a hardware-constrained environment. To address this issue and enhance the applicability of artificial intelligence (AI), this paper proposes a localization algorithm that does not require additional hardware. Specifically, the angle between a node and the anchor nodes is estimated based on the received signal strength indication (RSSI). A subsequent localization strategy leverages the inferred angular relationships in conjunction with a bounding box. Experimental evaluations in three scenarios with varying number of nodes demonstrate that the proposed method achieves substantial improvements in localization accuracy, reducing the average error by 72.4% compared to the Min-Max and RSSI-based DV-Hop algorithms, respectively.