摘要众所周知，超音速枪械在射击时，子弹出膛后做超音速飞行会产生弹头激波信号。枪声识别系统可以通过对超音速弹头激波信号的包络特征来对枪械类型进行识别，以此辅助对射击点的声测定位，也有助于对弹道特征的理论研究。正是在这一背景下，本文对超音速弹头激波信号的波形包络特征进行了初步研究。63007

我们根据超音速弹头激波信号的检测方法，在同一环境下不同的采集系统位置录制了一组7.62毫米突击步枪的枪声信号。通过对该组实测数据的分析，详细讨论了采集装置位置等因素对枪声信号的影响，并定性描述和定量分析了该组实测超音速弹头激波信号的包络特征，尝试用matlab软件拟合了该组超音速弹头激波包络的特征波形，发现其存在固定的变化规律，即包络均可以用二项高斯函数来拟合表示，而高斯函数的系数受到采集系统与枪械膛口之间距离的影响。

毕业论文关键词  超音速  弹头激波信号   包络特征   拟合波形

毕业设计说明书（论文）外文摘要

Title  Analysis of supersonic bullet shock signal envelope characteristics 

Abstract As everyone knows, when the supersonic guns shot, the bullet will fly over the sound and produce bullet shock signal.The recognition system can identify the guns through the envelope characteristics of supersonic bullet shock signal and can be used to assist to locate the firing point.The envelope characteristics of supersonic bullet shock signal were studied under this background.

According to the detection method of supersonic bullet shock signal,we record a group of shot signal under different conditions of 7.62 mm rifle firing.Then according to the detection method of warhead shock wave signal.By analyzing the measured data,we discuss the effects of acquisition device location of the signal in detail, describe qualitatively and analysis quantitatively the envelope characteristics of the measured supersonic bullet shock signal.We try to use MATLAB to fit the characteristics of the supersonic bullet shock waveform envelope, found that it has changes of fixed,the envelope can be showed by Gauss function,and the coefficients of the Gauss function are affected by the distance between the acquisition system and the muzzle.

Keywords  Supersonic  Projectile shockwave signal  Envelope characteristics  Fitting the waveform

1 绪论 1

1．1 研究意义与背景 1

1．2 国内外研究动态 1

1．3 论文主要工作和组织结构 4

2 超音速弹头激波信号的产生以及检测识别原理 4

2．1 超音速弹头激波信号的产生 5

2．2 超音速弹头激波信号检测 8

2．3 超音速弹头激波信号识别 10

3 超音速弹头激波信号的采集与分析 11

3．1 超音速弹头激波信号采集 11

3.1.1  便携式麦克风阵列音频信号采集系统 11

3.1.2  采集试验环境 12

3．2 超音速弹头激波信号的分析 13

3.2.1  建筑物对超音速弹头激波信号的影响 13

3.2.2  麦克风到弹道和射击者的距离对超音速弹头激波信号的影响 14

3.2.3  盲区信号分析