Academic Journal
Passive underwater tracking with unknown measurement noise statistics using variational Bayesian approximation
| العنوان: | Passive underwater tracking with unknown measurement noise statistics using variational Bayesian approximation |
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| المؤلفون: | Das, Shreya, Kumar, Kundan, Bhaumik, Shovan |
| المساهمون: | Department of Electrical Engineering and Automation, Sensor Informatics and Medical Technology, Indian Institute of Technology Patna, Aalto-yliopisto, Aalto University |
| بيانات النشر: | Elsevier Inc. |
| سنة النشر: | 2024 |
| المجموعة: | Aalto University Publication Archive (Aaltodoc) / Aalto-yliopiston julkaisuarkistoa |
| مصطلحات موضوعية: | Adaptive filtering, Bearings-only tracking, Gaussian filters, Normal inverse Wishart, Target motion analysis, Variational Bayesian approximation |
| الوصف: | Publisher Copyright: © 2024 Elsevier Inc. ; This paper considers a bearings-only tracking problem with unknown measurement noise statistics. It is assumed that the measurement noise follows a Gaussian probability density function where the mean and the covariance of the noise are unknown. Here, an adaptive nonlinear filtering technique is proposed, where the joint distribution of the measurement noise mean and its covariance are considered to follow a normal inverse Wishart (NIW) distribution. Using the variational Bayesian (VB) approximation, joint distribution of the target state, the measurement noise mean and covariance is factorized as the product of their individual probability density function (pdf). Minimizing the Kullback-Leibler divergence (KLD) between the factorized and true joint pdfs, probability distributions of the noise mean, covariance and the target states are evaluated. The estimation of states with the proposed VB based method is compared with the maximum a posteriori (MAP) and the maximum likelihood estimation (MLE) based adaptive filtering. Deterministic sigma points are used to realize the filtering algorithms. The proposed adaptive filter with VB approximation is found to be more accurate compared to their corresponding MAP-MLE based counterparts. ; Peer reviewed |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1051-2004 |
| Relation: | Digital Signal Processing: A Review Journal; Volume 153; Das, S, Kumar, K & Bhaumik, S 2024, ' Passive underwater tracking with unknown measurement noise statistics using variational Bayesian approximation ', Digital Signal Processing: A Review Journal, vol. 153, 104648 . https://doi.org/10.1016/j.dsp.2024.104648; PURE UUID: 87f48934-b8c5-4624-b96a-ce8920efa1ec; PURE ITEMURL: https://research.aalto.fi/en/publications/87f48934-b8c5-4624-b96a-ce8920efa1ec; PURE LINK: http://www.scopus.com/inward/record.url?scp=85196480429&partnerID=8YFLogxK; https://aaltodoc.aalto.fi/handle/123456789/129501; URN:NBN:fi:aalto-202407055088 |
| DOI: | 10.1016/j.dsp.2024.104648 |
| الاتاحة: | https://aaltodoc.aalto.fi/handle/123456789/129501 https://doi.org/10.1016/j.dsp.2024.104648 |
| Rights: | embargoedAccess |
| رقم الانضمام: | edsbas.CABBE19 |
| قاعدة البيانات: | BASE |
| تدمد: | 10512004 |
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| DOI: | 10.1016/j.dsp.2024.104648 |