Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Electrical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
JASA Express Lett. 2021 Dec;1(12):124802. doi: 10.1121/10.0009083.
A library of broadband (100-1000 Hz) channel impulse responses (CIRs) estimated between a short bottom-mounted vertical line array (VLA) in the Santa Barbara channel and selected locations along the tracks of 27 isolated transiting ships, cumulated over nine days, is constructed using the ray-based blind deconvolution algorithm. Treating this CIR library either as data-derived replica for broadband matched-field processing (MFP) or training data for machine learning yields comparable ranging accuracy (∼50 m) for nearby vessels up to 3.2 km for both methods. Using model-based replica of the direct path only computed for an average sound-speed profile comparatively yields∼110 m ranging accuracy.
使用基于射线的盲反卷积算法，构建了一个由圣巴巴拉海峡中短底部安装的垂直线列阵（VLA）和 27 艘孤立过境船只的轨道上的选定位置之间估计的宽带（100-1000 Hz）信道脉冲响应（CIR）库。将此 CIR 库视为宽带匹配场处理（MFP）的衍生数据副本，或机器学习的训练数据，两种方法对于附近船只的测距精度（约 50m）都相当，对于 3.2km 以外的船只也有类似的效果。仅针对平均声速剖面计算的直达路径的基于模型的副本，其测距精度约为 110m。
