计算机科学
异方差
稳健性(进化)
噪音(视频)
贝叶斯概率
声学
源字段
算法
人工智能
近场和远场
物理
机器学习
光学
生物化学
基因
图像(数学)
化学
作者
Kay L. Gemba,Santosh Nannuru,Peter Gerstoft
出处
期刊:Journal of the Acoustical Society of America
[Acoustical Society of America]
日期:2018-09-01
卷期号:144 (3_Supplement): 1943-1943
被引量:2
摘要
Using simulations and data, we localize a quiet source in the presence of an interferer. The SWellEx-96 Event S59 consists of a submerged source towed along an isobath over a 65 min duration with an interferer traversing the source track. This range independent, multi-frequency scenario includes mismatch, non-stationary noise, and operational uncertainty. Mismatch is defined as a misalignment between the actual source field observed at the array and the modeled replica vector. The noise process changes likely with time. This is modelled as a heteroscedastic Gaussian process, meaning that the noise variance is non-stationary across snapshots. Sparse Bayesian learning (SBL) has been applied previously to the matched field processing application [Gemba et al, J. Acoust. Soc. Am., 141:3411-3420, 2017]. Results demonstrate that SBL exhibits desirable robustness properties and improved localization performance when compared to the white noise constraint and Bartlett processors.
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