Localization for mixed near-field and far-field sources using data supported optimization

• المؤلفون الرئيسيون: Wen, Fuxi, Tay, Wee Peng
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2013
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/96421; http://hdl.handle.net/10220/10631; http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6289831&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F6269381%2F6289713%2F06289831.pdf%3Farnumber%3D6289831

Recently, localization for the coexistence of the far-field and near-field sources has received more attentions. In this paper, a maximum likelihood (ML) localization method using data supported optimization is considered. The range and direction of arrival (DOA) of the sources are estimated sequent...