基于ZYNQ的枪声识别系统设计
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1.中北大学省部共建动态测试技术国家重点实验室 太原 030051; 2.中北大学信息探测与处理山西省重点实验室 太原 030051

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TJ206

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国家自然科学基金(62101512)、山西省青年科学基金(20210302124031)项目资助


Design of gun sound recognition system based on ZYNQ
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1.State Key Laboratory of Dynamic Testing Technology,North University of China,Taiyuan 030051,China; 2.Key Laboratory of Information Detection and Processing of Shanxi Province,North University of China,Taiyuan 030051,China

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    摘要:

    枪声识别技术在军事环境下可以快速准确地提供战场信息,但是目前大部分枪声识别系统均部署在服务器端,实用性和可行性不高,针对这一问题,本文设计了一种基于ZYNQ的枪声识别系统。该系统以ZYNQ7020芯片为核心,充分利用ZYNQ芯片集ARM与FPGA于一体的特性,首先在芯片的FPGA部分设计了多通道数据传输链路和声场特征参数提取模块;其次在芯片的ARM部分部署经过PC端训练后的轻量化网络模型,对经过FPGA提取的特征参数进行处理,进而实现对枪声种类的识别;最后使用枪声数据集NIJ Grant 2016-DN-BX-0183中的3种枪声在外场进行试验。试验结果表明,该系统能够准确地对枪声进行分类,枪声的平均识别率达到91.67%。该成果在枪声识别领域具有较强的应用价值。

    Abstract:

    Gunshot recognition technology can quickly and accurately provide battlefield information in a military environment, but most gunshot recognition systems are currently deployed on the server side, which is not practical and feasible. To solve this problem, this paper designs a ZYNQbased technology gun sound recognition system. The system takes ZYNQ7020 chip as the core, and makes full use of the ZYNQ chip that integrates ARM and FPGA. First, a multi-channel data transmission link and a sound field feature parameter extraction module are designed in the FPGA part of the chip. Secondly, the ARM part of the chip is deployed after the lightweight network model trained on the PC side processes the feature parameters extracted by the FPGA to identify the types of gunshots. Finally, the three gunshots in the gunshot dataset NIJ Grant 2016-DN-BX-0183 are used. Test in the field. The test results show that the system can accurately classify gunshots, and the average recognition rate of gunshots reaches 91.67%. This achievement has strong application value in the field of gunshot recognition.

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孙袖山,李剑,贺斌,庞润嘉,马翊翔,郭锦铭.基于ZYNQ的枪声识别系统设计[J].电子测量技术,2023,46(2):1-6

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  • 在线发布日期: 2024-03-11
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