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Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

التفاصيل البيبلوغرافية
العنوان: Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference
المؤلفون: Libin Du, Huming Li, Lei Wang, Xu Lin, Zhichao Lv
المصدر: Remote Sensing, Vol 15, Iss 13, p 3222 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
مصطلحات موضوعية: array signal processing, sparse Bayesian learning, direction estimation, pulse noise, Science
الوصف: Pulse noise (such as glacier fracturing and offshore pile driving), commonly seen in the marine environment, seriously affects the performance of Direction-of-Arrival (DOA) estimation methods in sonar systems. To address this issue, this paper proposes a high robustness underwater target estimation method based on variational sparse Bayesian inference by studying and analyzing the sparse prior assumption characteristics of signals. This method models pulse noise to build an observation signal, completes the derivation of the conditional distribution of the observed variables and the prior distribution of the sparse signals, and combines Variational Bayes (VB) theory to approximate the posterior distribution, thereby obtaining the recovered signal of the sparse signals and reducing the impact of pulse noise on the estimation system. Our simulation results showed that the proposed method achieved higher estimation accuracy than traditional methods in both single and multiple snapshot scenarios and has practical potential.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 15133222
2072-4292
Relation: https://www.mdpi.com/2072-4292/15/13/3222; https://doaj.org/toc/2072-4292
DOI: 10.3390/rs15133222
URL الوصول: https://doaj.org/article/2e45cb20372944f5a814cb39fe958ae1
رقم الأكسشن: edsdoj.2e45cb20372944f5a814cb39fe958ae1
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15133222
20724292
DOI:10.3390/rs15133222