Underwater target classification using passive sonar remains a critical issue due to the
changeable ocean environment. Convolutional neural networks (CNNs) have shown …

The problem of radar target classification is examined for the case when more than one
perspective or viewing angle of the target is available to the sensor. Using full-scale target …

Since the expensive annotation of high-quality signals obtained from passive sonars and the
weak generalization ability of the single feature in the ocean, this paper proposes the self …

Hidden Markov models (HMMs) have previously been successfully applied to subsurface
threat detection using ground penetrating radar (GPR) data. However, parameter estimation …

The information content of radar target signatures is a key aspect for automatic target
recognition. The role of high-range resolution is investigated as a function of the illuminating …

针对雷达高分辨率距离像(HRRP) 数据的识别问题, 该文利用HRRP 生成的时序特性,
提出一种基于循环神经网络的注意模型. 该模型利用具有记忆功能的循环神经网络对时域数据 …

In this paper, we propose a multistep information fusion scheme for target detection through
foliage and wall, using ultrawideband (UWB) radar sensor networks. We apply an …

A new adaptive strategy for performing data collection with a sonar-equipped autonomous
underwater vehicle (AUV) is proposed. The approach is general in the sense that it is …

To improve the performance of radar High-Resolution Range Profile (HRRP) target
recognition, a new attention-based model is proposed based on time domain feature. This …

The problem of classifying targets in sonar images from multiple views is modeled as a
partially observable Markov decision process (POMDP). This model allows one to adaptively …