multiple objective optimization
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Fuel ◽  
2022 ◽  
Vol 308 ◽  
pp. 122041
Author(s):  
R.S.R.M. Hafriz ◽  
N.A. Arifin ◽  
A. Salmiaton ◽  
R. Yunus ◽  
Y.H. Taufiq-Yap ◽  
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2021 ◽  
Vol 105 ◽  
pp. 104439
Author(s):  
Tram Nguyen ◽  
Toan Bui ◽  
Hamido Fujita ◽  
Tzung-Pei Hong ◽  
Ho Dac Loc ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaolong Li ◽  
Yi Xing ◽  
Zhenkai Zhang

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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