Abstract

PurposeThe passive source localization (PSL) problem using angles of arrival (AOA), time differences of arrival (TDOA) or gain ratios of arrival (GROA) is generally nonlinear and nontrival. In this research, the purpose of this paper is to design an accurate hybrid source localization approach to solve the PSL problem. The inspiration is drawn from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.Design/methodology/approachThe maximum-likelihood (ML) method is reexamined by using hybrid measurements. Being assisted by the bearings, a new hybrid weighted least-squares (WLS) method is then proposed by jointly utilizing the bearing, TDOA and GROA measurements.FindingsTheoretical performance analysis illustrates that the mean-square error of the ML or WLS method can attain the Cramér-Rao lower bound for Gaussian noise over small error region. However, the WLS method has much lower computational complexity than the ML algorithm. Compared with the AOA-only, TDOA-only, AOA-TDOA, TDOA-GROA methods, the localization accuracy can be greatly improved by combining the AOAs, TDOAs and GROAs, especially for some specific geometries.Originality/valueA novel bearing-assisted TDOA-GROA method is proposed for source localization, and a new hybrid WLS estimator is presented inspired from the fact that the bearings, TDOAs and GROAs are complementary in terms of their geometry properties.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.