Ship Target Classification and Identification Based on MVDR Spectral Parameters

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Ship Target Classification and Identification Based on MVDR Spectral Parameters

更新时间：2026-09-04

- Ship Target Classification and Identification Based on MVDR Spectral Parameters
- Vol. 33, Issue 10, Pages: 159-162(2016)
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- Published：2016
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基于MVDR参数谱在舰船目标识别中的应用[J]. 微电子学与计算机, 2016, 33(10): 159-162.

Ship Target Classification and Identification Based on MVDR Spectral Parameters[J]. 2016, 33(10): 159-162.
基于MVDR参数谱在舰船目标识别中的应用[J]. 微电子学与计算机, 2016, 33(10): 159-162. DOI：

Ship Target Classification and Identification Based on MVDR Spectral Parameters[J]. 2016, 33(10): 159-162. DOI：

摘要

现代海战中如何在复杂多变的海洋环境中提取有效的舰船目标识别特征是被动声纳目标识别的关键环节.首先介绍了舰船辐射目标信号的最小均方无失真响应(Minimum Variance Distortionless Response

MVDR)谱分析的模型方法

然后通过对比分析了三类目标MVDR、FFT和LP谱之间的关系发现最小方差无失真响应滤波器能提供一个更好的舰船目标辐射噪声频谱包络

随后比较分析阶数对性能的影响

发现随着滤波器阶数的增加其目标信号频谱包络的效果更好.最后将提取的LP谱特征与MVDR谱特征应用到BP神经网络进行分类识别

实验结果发现

MVDR谱特征的识别率高于LP谱特征得到了很好的分类效果.

Abstract

In the modern ocean battle

how to extract features of ship targets during the complicated and changeable sea environment is a real key for passive sonar underwater target identification. This paper firstly discusses Minimum Variance Distortionless Response Modeling method of ship target. Then

Comparing with the MVDR

FFT and LP modeling method

MVDR is found to provide better spectrum envelop of ship radiated noise

and it analyses the influence of the order number on the performance which is found that it can provide better spectrum envelop of ship radiated noise with the increase of the filter order. Finally

the designed BP neural network is adopted to classify and identify MVDR spectrum characteristics and LP spectrum characteristics. Based on processing results of experimental data

the MVDR spectral parameters proposed in this paper has better classification effect and higher reliability than LP spectrum.

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