构建32类无人机声学数据集并开发可交互分析工具
A Multiclass Acoustic Dataset and Interactive Tool for Analyzing Drone Signatures in Real-World Environments
- 收集32种不同品牌型号的无人机原始音频与声谱图
- 提供听音、看频谱、查梅尔频率倒谱系数的交互功能
- 适合研究无人机检测、声学分类及教学演示者使用
无人机在各行业快速普及，带来隐私、安全和噪音污染等挑战。现有基于视觉与雷达的检测系统在特定条件下受限，亟需有效的声学检测方法。本文构建了一个涵盖32种不同品牌与型号无人机声学特征的综合性数据集，包含原始音频、频谱图和梅尔频率倒谱系数（MFCC）图。同时推出一个交互式网页应用，支持用户按类别选择无人机，收听音频并查看对应频谱与MFCC图。该工具旨在促进无人机检测、分类与声学分析研究，推动技术进步与教育应用。论文详述数据集构建流程、网页应用设计实现，并展示实验结果与用户反馈。最后讨论潜在应用场景与未来扩展方向。
原文摘要 · Abstract (English)
The rapid proliferation of drones across various industries has introduced significant challenges related to privacy, security, and noise pollution. Current drone detection systems, primarily based on visual and radar technologies, face limitations under certain conditions, highlighting the need for effective acoustic-based detection methods. This paper presents a unique and comprehensive dataset of drone acoustic signatures, encompassing 32 different categories differentiated by brand and model. The dataset includes raw audio recordings, spectrogram plots, and Mel-frequency cepstral coefficient (MFCC) plots for each drone. Additionally, we introduce an interactive web application that allows users to explore this dataset by selecting specific drone categories, listening to the associated audio, and viewing the corresponding spectrogram and MFCC plots. This tool aims to facilitate research in drone detection, classification, and acoustic analysis, supporting both technological advancements and educational initiatives. The paper details the dataset creation process, the design and implementation of the web application, and provides experimental results and user feedback. Finally, we discuss potential applications and future work to expand and enhance the project.
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