Research Article
Convex Optimization Algorithm for Wireless Localization by Using Hybrid RSS and AOA Measurements
@INPROCEEDINGS{10.1007/978-3-030-36442-7_3, author={Lufeng Mo and Xiaoping Wu and Guoying Wang}, title={Convex Optimization Algorithm for Wireless Localization by Using Hybrid RSS and AOA Measurements}, proceedings={Broadband Communications, Networks, and Systems. 10th EAI International Conference, Broadnets 2019, Xi’an, China, October 27-28, 2019, Proceedings}, proceedings_a={BROADNETS}, year={2019}, month={12}, keywords={Wireless localization Received signal strength Angle of arrival Convex optimization}, doi={10.1007/978-3-030-36442-7_3} }- Lufeng Mo
Xiaoping Wu
Guoying Wang
Year: 2019
Convex Optimization Algorithm for Wireless Localization by Using Hybrid RSS and AOA Measurements
BROADNETS
Springer
DOI: 10.1007/978-3-030-36442-7_3
Abstract
With the development of new array technology and smart antenna, it is easier to obtain the angle of arrival (AOA) measurements. The hybrid received signal strength (RSS) and AOA measurement techniques are proposed for the wireless localization in the paper. By converting the measurement equations and relaxing the optimization function, a second order cone programming and semidefinite programming (SOCPSDP) algorithm is put forward to obtain the position estimate by considering the known or unknown transmit power. The proposed SOCPSDP algorithm provides a solution to the source position estimate and avoids the initialization process. The simulations show that the SOCPSDP algorithm performs better than the semidefinite programming (SDP) algorithm. The accuracy performance of the proposed SOCPSDP algorithm degrades as the measurement noises increase.