An Efficient Direct Position Determination Algorithm Combined with Time Delay and Doppler

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• 作者：Yun Long Wang ; Ying Wu ; Shan Chao Yi
• 关键词：Direct position determination ; Maximum likelihood ; Passive location ; Eigenvalue decomposition
• 刊名：Circuits, Systems, and Signal Processing
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：35
• 期：2
• 页码：635-649
• 全文大小：884 KB
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• 作者单位：Yun Long Wang (1)
  Ying Wu (1)
  Shan Chao Yi (1)
  
  1. Zhengzhou Information Science and Technology Institute, Zhengzhou, 450000, People’s Republic of China
  
• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  
• 出版者：Birkh盲user Boston
• ISSN：1531-5878

文摘

The conventional passive location methods such as Taylor series and two-step weighted least square are usually implemented by first estimating related parameters and then solving equations to get the target position. However, the parameters used for location estimation are only estimates and represent an unnecessary intermediate step in the process, which also cannot guarantee to match the real location information. This separation between the parameter estimation algorithm and the location estimation algorithm may lead to information loss. By utilizing a combination of time delay and Doppler, this paper proposes an improved direct position determination algorithm to improve the estimation accuracy. A novel maximum likelihood estimator is used to transform the problem into one of searching for the largest eigenvalue of a Hermitian matrix of position information. Calculation is simplified since the part of nonzero eigenvalues remains unchanged after the matrix is transposed. The target’s position estimation is then determined by searching the space of two-dimensional geographic grids. Simulation results show that the performance of proposed algorithm is closer to the Cramér–Rao lower bound than the original direct position determination algorithm and traditional two-step method based on time delay and Doppler.