Maximum likelihood estimation of multiple sources using a local optimization method

1996 ◽  
Vol 79 (11) ◽  
pp. 14-24
Author(s):  
Shin'Ichi Sawamura ◽  
Hisashi Kanda ◽  
Yoshikazu Miyanaga ◽  
Koji Tochinai
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Optimization Method ◽  
Local Optimization ◽  
Multiple Sources ◽  
Local Optimization Method

scholarly journals A Geometric Calibration Method of Hydrophone Array Based on Maximum Likelihood Estimation with Sources in Near Field

2020 ◽  
Vol 8 (9) ◽  
pp. 678
Author(s):  
Nan Zou ◽  
Zhenqi Jia ◽  
Jin Fu ◽  
Jia Feng ◽  
Mengqi Liu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Signal To Noise Ratio ◽  
Near Field ◽  
Likelihood Estimation ◽  
Calibration Method ◽  
Optimization Method ◽  
High Signal ◽  
Geometric Calibration ◽  
Environment Experiment

Considering the requirement of the near-field calibration under strong underwater multipath condition, a high-precision geometric calibration method based on maximum likelihood estimation is proposed. It can be used as both auxiliary-calibration and self-calibration. According to the near-field geometry error model, the objective function of nonlinear optimization problem is constructed by using the unconditional maximum likelihood estimator. The influence of multipath on geometric calibration is studied. The strong reflections are considered as the coherent sources, and the compensation strategy for auxiliary-calibration is realized. The optimization method (differential evolution, DE) is used to solve the geometry errors and sources’ position. The method in this paper is compared with the eigenvector method. The simulation results show that the method in this paper is more accurate than the eigenvector method especially under high signal-to-noise ratio (SNR) and multipath environment. Experiment results further verify the effectiveness.

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