New Application of the Hybrid Localization Algorithm of TDOA and AOA

Nanchao Luo

doi:10.20965/jaciii.2019.p0134

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JACIII Vol.23 No.1 pp. 134-138

doi: 10.20965/jaciii.2019.p0134

(2019)

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New Application of the Hybrid Localization Algorithm of TDOA and AOA

Nanchao Luo

School of Mathematics and Computer Science, Aba Teachers University
Wenchuan, Sichuan 623002, China

Received:

May 17, 2018

Accepted:

July 9, 2018

Published:

January 20, 2019

Keywords:

wireless sensor, location algorithm, network

Abstract

The location algorithm based on arrival time difference has high complexity and high system power consumption. When using the traditional TDOA positioning algorithm to locate, we will encounter over-determined nonlinearity of positioning equation, and you need to use iterative method to solve it. Based on this, this paper proposed a hybrid positioning algorithm of TDOA and AOA. Combining the TDOA and AOA information, the problem of solving the iterative positioning equation was simplified successfully, which reduced the complexity of the algorithm and reduced the system power consumption. At the same time, in order to solve the problem of high system power consumption, this paper also proposed the use of Zigbee protocol instead of the traditional Wi-Fi protocol to develop the positioning system, thereby effectively reducing system power consumption, increasing system life and improving system applicability.

Cite this article as:

N. Luo, “New Application of the Hybrid Localization Algorithm of TDOA and AOA,” J. Adv. Comput. Intell. Intell. Inform., Vol.23 No.1, pp. 134-138, 2019.

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References

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[9] P. C. Shill et al., “Optimization of Fuzzy Logic Controller for Trajectory Tracking Using Genetic Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.6, pp. 639-651, 2011.
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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] M. Raj et al., “Using data mules to preserve source location privacy in Wireless Sensor Networks,” Pervasive and Mobile Computing, Vol.11, pp. 244-260, 2017.

[2] [2] R. Di Pietro and A. Viejo, “Location privacy and resilience in wireless sensor networks querying,” Computer Communications, Vol.34, No.3, pp. 515-523, 2016.

[3] [3] G.-Z. Chen, C.-F. Shen, and L.-J. Zhou, “Design and performance analysis of wireless sensor network location node system for underground mine,” Mining Science and Technology, Vol.19, No.6, pp. 813-818, 2017.

[4] [4] A. A. Nezhad, A. Miri, and D. Makrakis, “Location privacy and anonymity preserving routing for wireless sensor networks,” Computer Networks, Vol.52, Issue 18, pp. 3433-3452, 2017.

[5] [5] C. N. Nyirenda et al., “A Fuzzy Multiobjective Particle Swarm Optimized TS Fuzzy Logic Congestion Controller for Wireless Local Area Networks,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.1, pp. 41-54, 2011.

[6] [6] E. Ekici et al., “Secure probabilistic location verification in randomly deployed wireless sensor networks,” Ad Hoc Networks, Vol.6, No.2, pp. 195-209, 2016.

[7] [7] Y. Yan et al., “Hierarchical location service for wireless sensor networks with mobile sinks,” Wireless Communications and Mobile Computing, Vol.10, No.7, pp. 56-57, 2016.

[8] [8] H. C. Leligou et al., “Combining trust with location information for routing in wireless sensor networks,” Wireless Communications and Mobile Computing, Vol.12, Issue 12, pp. 1091-1103, 2012.

[9] [9] P. C. Shill et al., “Optimization of Fuzzy Logic Controller for Trajectory Tracking Using Genetic Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.15, No.6, pp. 639-651, 2011.

[10] [10] E. C.-H. Ngai and I. Rodhe, “On providing location privacy for mobile sinks in wireless sensor networks,” Wireless Networks, Vol.19, No.1, pp. 115-130, 2013.