被动声呐

基于进化规划的Kohonen网络用于被动声呐目标聚类研究

Evolutionary Programming Based Kohonen Network for Passive Sonar Targets Clustering Analysis

被动声呐目标识别技术的现状与展望

Status and prospects on techniques of recognition for passive sonar targets

本文针对被动声呐目标识别，首先着重研究了调制线谱特征提取方法，然后为了训练神经网络目标分类器，本文将遗传算法和BP算法相结合，提出了一种新的自适应遗传BP算法。

Ln this paper , a feature extraction method of modulation line spectrum is studied at first , and then a novel adaptive genetic backpropagation algorithm is proposed for training neural network target classifier .

为解决被动声呐目标的特征提取与识别问题，通过对被动声呐目标噪声频谱特性的深入分析，给出了一种基于Welch谱估计的目标特征提取方法。

In order to solve the problem of the underwater target feature extraction and recognition , this paper analyzed the frequency spectrum signature of the passive sonar target noise , and proposed a kind of method to extract the object signature based on Welch power spectrum density estimation .

主被动声呐多目标航迹关联的双门限算法研究

Study on Double-threshold Tracks Correlation Algorithm for Active Sonar to Passive Sonar

一种主/被动声呐目标回波信号模拟器的研制

Development of a Kind of Active and Passive Sonar Target Echo Signal Simulator

研究结果可以用于被动声呐目标识别。

The research results can be applied to the passive sonar target recognition .

被动声呐是现代水声对抗最重要的探测装备。

Passive sonar is the most important detecting equipment in modern underwater acoustical countermeasure .

被动声呐目标识别系统中目标分类器的设计和训练是一项重要内容。

The targets classifier is a key element in passive Sonar target recognition systems .

本文首先从理论出发，讨论了被动声呐检测的国内外研究现状、实现的意义，以及其基本理论。

Firstly , the status quo and basic theory of passive sonar technology are described .

研究了被动声呐探测距离预报的仿真技术。

The simulation techniques for forecasting the detection range of passive sonar are studied in the paper .

本文从提高被动声呐的检测性能出发，提出了超增益阵的设计。

In this dissertation , we study a supergain hydrophone array to improve the detection performance of passive sonar .

早期的被动声呐只能测目标的方位，不能测目标的距离。

Earlier passive sonar could only estimate the azimuth of a target , but not to range for any targets .

随着舰船噪声的降低，对被动声呐的检测性能提出了巨大的挑战。

Along with the decreasing noise radiation of underwater vessels , it appears a big challenge to the passive sonar .

传统被动声呐系统多半采用中小规模集成电路，体积较大，硬件处理能力低。

The traditional SONARs are consisted of middle or small scale Integrated circuit . Their hardware is big and low calculation ability .

误差反传神经网络在被动声呐目标分类中得到了广泛的应用，但该算法在搜索过程中容易陷入局部最小值，同时使用赢者独活的识别决策策略，导致识别率的下降。

Though Back-Propagation neural network is widely used in passive sonar target classification , it tends to come into the local minimum value .

舰船、鱼雷和潜艇等目标所辐射的噪声，是被动声呐赖以探测的信号源。

The radiation noise generated by ships , torpedoes , submarines and other objectives is the crucial signal sources for passive sonar detection .

但是迄今为止，被动声呐仍然局限于检测宽带目标，对于脉冲目标没有跟踪定位的能力。

However , all of the passive sonars are constrained to range broadband targets only , remaining useless in ranging for impulse targets up till now .

总之，文章从理论、仿真、实验数据处理等各方面都证实超增益处理可以大大提高被动声呐的检测性能。

In summary , in this dissertation it is proved by theory deducing ~ computer simulations and real-data processing that supergain processing can improve the detection performance of passive sonar significantly .

讨论了在被动声呐目标识别任务中应用听觉模型的可能性，同时，结合声呐目标识别的特点，对听觉外周模型的适用性建模研究，提出了若干建议。

Then , its possibility in passive sonar target classification is discussed , and some proposals are given for the adaptation of the modeling , according to the specialties of sonar processing .

最后，对海上实录的三类目标噪声进行了分类识别，实验结果表明本文设计的被动声呐目标识别系统具有很好的分类效果。

At last , the classification experiment for three different classes of targets is done , results of experiment show that the passive sonar target recognition system designed in the paper has higher correct classification rate ?

为了提高水面舰艇在未来水声对抗作战中的生存能力，本文在分析低频噪声干扰器工作机理的基础上，分别研究了噪声干扰器对抗主被动声呐的效果，计算出干扰器的有效干扰区域。

In order to improve the survival capability of naval vessels in hydroacoustic countermeasure warfare , based on the low frequency noise-jammer 's working principle , the effectiveness is researched and the valid interference area is presented .

将该方法用于被动声呐目标的分类识别，实验结果表明基于进化规则的自适应高斯神经网络能够有效的克服局部最小问题，具有更好的识别率。

This kind of adaptive Gauss neural network is used to classify passive sonar target , the result of experiment shows that the adaptive Gauss neural network based on evolutionary programming can solve the local extreme value problem and be more effective in classification .

卡尔曼滤波在被动测距声呐中的应用

The Application of Kalman Filter in Passive Ranging Sonars

被动测距声呐中信号模糊对时延估计的影响

The Influence of Signal Ambiguous to the Time Delay Estimation in Passive Ranging Sonars

本文提出了一种在被动数字声呐中利用相邻三个差波束响应精确测向的原理；

This paper discusses the problem of orientating and tracing multiple targets for multibeam digital sonar .

声呐测量数据中异常值的辨识方法被动测距声呐中的关键技术问题是对两对水听器所接收信号的时间差进行估计。

A method for identifying outliers in data observed from sonars The Time Delay Estimation ( TDE ) is very important in passive ranging sonars .

被动合成孔径声呐阵列目标远程定位

Long Distance Source Localization with Passive Synthetic Aperture Sonar

主被动拖线阵声呐中拖曳平台噪声和拖鱼噪声在浅海使用时的干扰特性

The interference characteristics of platform and towed body noise in shallow water for active / passive towed array sonar

噪声被动测距一直是水声信号处理领域内非常活跃的一个课题，但是被动声呐原有系统采用中小规模集成电路，机柜较大；

Noise Passive-ranging is always an active research problem in underwater acoustic signal processing domain .