Localizing a quiet moving source with range-coherent matched field processing

2021 ◽  
Vol 150 (4) ◽  
pp. A277-A277
Author(s):  
Franklin H. Akins ◽  
William Kuperman
Keyword(s):  
Matched Field Processing ◽  
Moving Source

Matched field processing for a moving source

1989 ◽  
Vol 85 (S1) ◽  
pp. S16-S17
Author(s):  
John M. Ozard ◽  
Gary H. Brooke ◽  
Scott Tinis
Keyword(s):  
Matched Field Processing ◽  
Moving Source

scholarly journals Matched Field Processing Based on Bayesian Estimation

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1374
Author(s):  
Guolei Zhu ◽  
Yingmin Wang ◽  
Qi Wang
Keyword(s):  
Gaussian Noise ◽  
Posterior Probability ◽  
Side Lobe ◽  
Positioning Accuracy ◽  
Matched Field Processing ◽  
Moving Source ◽  
Bayesian Criterion ◽  
Posterior Probability Density ◽  
Ocean Environment ◽  
Localization And Tracking

In order to improve the robustness and positioning accuracy of the matched field processing (MFP) in underwater acoustic systems, we propose a conditional probability constraint matched field processing (MFP-CPC) algorithm in this paper, which protects the main-lobe and suppresses the side-lobe to the AMFP by the constraint parameters, such as the posterior probability density of source locations obtained by Bayesian criterion under the assumption of white Gaussian noise. Under such constraint, the proposed MFP-CPC algorithm not only has the same merit of a high resolution as AMFP but also improves the robustness. To evaluate the algorithm, the simulated and experimental data in an uncertain shallow ocean environment is used. From the results, MFP-CPC is robust to the moored source, as well as the moving source. In addition, the localization and tracking performances of using the proposed algorithm are consistent with the trajectory of the moving source.

Matched‐field processing for a moving source

1992 ◽  
Vol 92 (1) ◽  
pp. 403-417 ◽  
Author(s):  
Cedric A. Zala ◽  
John M. Ozard
Keyword(s):  
Matched Field Processing ◽  
Moving Source

Synthetic adaptive matched field processing for moving source with a horizontal line array

2021 ◽  
Vol 149 (2) ◽  
pp. 1138-1146
Author(s):  
Fenghua Li ◽  
Feilong Zhu ◽  
Yanjun Zhang ◽  
Bo Zhang ◽  
Wen Li ◽  
...  
Keyword(s):  
Horizontal Line ◽  
Matched Field Processing ◽  
Moving Source ◽  
Line Array

LOW COMPLEXITY DOA LIKE HUMAN

2020 ◽  
Author(s):  
Mike Hugo
Keyword(s):  
Time Delays ◽  
Low Complexity ◽  
Moving Source

The proposed \gls{cimpl} strategy is customized toward binaural portable amplifier frameworks with receiver exhibits in every unit. The technique uses the roundabout insights (roundabout mean and round difference) of \gls{impd} across various amplifier sets. These \gls{impd}s are right off the bat mapped to time delays through a difference weighted direct fit, at that point mapped to azimuth \gls{doa} and finally data of various mouthpiece sets is consolidated. The fluctuation is helped through the various changes and goes about as an unwavering quality list of the evaluated point. Both the subsequent edge and fluctuation are taken care of into a wrapped Kalman channel, which gives a smoothed gauge of the \gls{doa}. The proposed strategy improves the exactness of the followed point of a solitary moving source contrasted and the benchmark technique gave by the LOCATA challenge, and it runs around multiple times quicker.

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