A Hybrid AOA and TDOA-Based Localization Method Using Only Two Stations

Target localization plays an important role in the application of radar, sonar, and wireless sensor networks. In order to improve the localization performance using only two stations, a hybrid localization method based on angle of arrival (AOA) and time difference of arrival (TDOA) measurements is proposed in this paper. Firstly, the optimization model for localization based on AOA and TDOA are built, respectively, in the sensor network. Secondly,the majorization-minimization (MM) method is employed to create surrogate functions for solving the multiple objective optimization problem. Next, the hybrid localization problem is solved by the projected gradient decent (PGD) method. Finally, the Cramer–Rao lower bound (CRLB) for the joint AOA and TDOA method is derived for the comparison. Simulations proved that the proposed method has improved localization performance using AOA and TDOA measurements from only two base stations.

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A Gossip-Based AOA Distributed Localization Algorithm for Wireless Sensor Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.577.841 ◽

2014 ◽

Vol 577 ◽

pp. 841-846 ◽

Cited By ~ 1

Author(s):

Wen Cui ◽

Shao Chuan Wu ◽

Yu Ze Wang

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Wireless Sensor ◽

Cooperative Localization ◽

Central Processor ◽

Localization Algorithm ◽

Angle Of Arrival ◽

Position Information ◽

Localization Method ◽

Gossip Algorithm

Position information of individual nodes is useful in implementing functions such as routing in wireless sensor networks. Distributed localization method has been widely concerned in the case of no central processor is available to handle the calculations in the networks. In this paper, we focus on distributed localization techniques based on angle of arrival information between neighboring nodes. A novel distributed cooperative localization method based on gossip algorithm is proposed, which can obviously improve the positioning performance of the previous methods.

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A NOVEL HYBRID LOCALIZATION METHOD FOR WIRELESS SENSOR NETWORK

International Journal on Smart Sensing and Intelligent Systems ◽

10.21307/ijssis-2017-920 ◽

2016 ◽

Vol 9 (3) ◽

pp. 1323-1340 ◽

Cited By ~ 3

Author(s):

Wang Jun ◽

Zhang Fu ◽

Ren Tiansi ◽

Chen Xun ◽

Liu Gang

Keyword(s):

Wireless Sensor Network ◽

Sensor Network ◽

Wireless Sensor ◽

Localization Method ◽

Hybrid Localization

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A hybrid localization method in wireless sensor networks

2011 International Conference on Networking, Sensing and Control ◽

10.1109/icnsc.2011.5874956 ◽

2011 ◽

Author(s):

Lichuan Liu ◽

Zaihan Jiang

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Wireless Sensor ◽

Localization Method ◽

Hybrid Localization

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Iterative Regression Based Hybrid Localization for Wireless Sensor Networks

Sensors ◽

10.3390/s21010257 ◽

2021 ◽

Vol 21 (1) ◽

pp. 257

Author(s):

Kyunghyun Lee ◽

Sangkyeum Kim ◽

Kwanho You

Keyword(s):

Optimal Solution ◽

Base Stations ◽

Recursive Least Squares ◽

Wireless Sensor ◽

Angle Of Arrival ◽

Rls Algorithm ◽

Recursive Solution ◽

Localization Scheme ◽

Computational Speed ◽

Noise Factors

Among various localization methods, a localization method that uses a radio frequency signal-based wireless sensor network has been widely applied due to its robustness against noise factors and few limits on installation location. In this paper, we focus on an iterative localization scheme for a mobile with a limited number of time difference of arrival (TDOA) and angle of arrival (AOA) data measured from base stations. To acquire the optimal location of a mobile, we propose a recursive solution for localization using an iteratively reweighted-recursive least squares (IR-RLS) algorithm. The proposed IR-RLS scheme can obtain the optimal solution with a fast computational speed when additional TDOA and/or AOA data is measured from base stations. Moreover, while the number of measured TDOA/AOA data was limited, the proposed IR-RLS scheme could obtain the precise location of a mobile. The performance of the proposed IR-RLS method is confirmed through some simulation results.

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