Localization in modified polar representation: hybrid measurements and closed-form solution  

作　　者：CONG Xunchao SUN Yimao YANG Yanbing ZHANG Lei CHEN Liangyin 

机构地区：[1]The 10th Research Institute of China Electronics Technology Group Corporation,Chengdu 610036,China [2]College of Computer Science and Institute for Industrial Internet Research,Sichuan University,Chengdu 610065,China

出　　处：《Journal of Systems Engineering and Electronics》2024年第3期575-588,共14页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China (62101359);Sichuan University and Yibin Municipal People’s Government University and City Strategic Cooperation Special Fund Project (2020CDYB-29);the Science and Technology Plan Transfer Payment Project of Sichuan Province (2021ZYSF007);the Key Research and Development Program of Science and Technology Department of Sichuan Province (2020YFS0575,2021KJT0012-2 021YFS-0067)。

摘　　要：Classical localization methods use Cartesian or Polar coordinates, which require a priori range information to determine whether to estimate position or to only find bearings. The modified polar representation (MPR) unifies near-field and farfield models, alleviating the thresholding effect. Current localization methods in MPR based on the angle of arrival (AOA) and time difference of arrival (TDOA) measurements resort to semidefinite relaxation (SDR) and Gauss-Newton iteration, which are computationally complex and face the possible diverge problem. This paper formulates a pseudo linear equation between the measurements and the unknown MPR position,which leads to a closed-form solution for the hybrid TDOA-AOA localization problem, namely hybrid constrained optimization(HCO). HCO attains Cramér-Rao bound (CRB)-level accuracy for mild Gaussian noise. Compared with the existing closed-form solutions for the hybrid TDOA-AOA case, HCO provides comparable performance to the hybrid generalized trust region subproblem (HGTRS) solution and is better than the hybrid successive unconstrained minimization (HSUM) solution in large noise region. Its computational complexity is lower than that of HGTRS. Simulations validate the performance of HCO achieves the CRB that the maximum likelihood estimator (MLE) attains if the noise is small, but the MLE deviates from CRB earlier.

关 键 词：LOCALIZATION modified polar representation time difference of arrival(TDOA) angle of arrival(AOA) closed-form solution 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置] TN929.5[自动化与计算机技术—控制科学与工程]