نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد دانشکده فنی و مهندسی دانشگاه خلیج فارس

2 استادیار دانشکده فنی و مهندسی دانشگاه خلیج فارس

3 دانشیار دانشکده فنی و مهندسی دانشگاه خلیج فارس

چکیده

تشخیص و طبقه‌بندی شناور های دریایی بر اساس نویز تشعشعی صوتی از آن‌ها از جمله ضرورت های سیستم های سوناری است. در این مقاله روش‌هایی که تاکنون در حوزه طراحی سیستم طبقه‌بندی اهداف سونار غیرفعال انجام شده است مورد بررسی قرار گرفته و الگوریتمی جدید ارائه گردیده است. در روش پیشنهادی با استفاده از الگوریتم استخراج ویژگی LDA و ترکیب ویژگی‌های تبدیل فوریه زمان کوتاه و طنین صوت، الگوریتم طبقه‌بندی با نام STFTLDA-Timb ارائه شده است که موجب استخراج ویژگی‌هایی با تفکیک پذیری بالا شده و صحت طبقه‌بندی را در مقایسه با سیستم‌های متداول مبتنی بر STFT تا %45/8 بهبود بخشیده است. الگوریتم پیشنهادی بر روی برخی داده های واقعی آزمایش شده و نتایج حاصله شده در مقایسه با الگوریتمهای طبقه‌بندی کننده رایج و پرکاربردی مثل طبقه‌بندی کننده‌های آماری، طبقه‌بندی کننده‌های شبکه عصبی و طبقه‌بندی‌کننده‌های تجمعی، نتایج بهتری را ارایه کرده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Passive Sonar Signals Classification using Fusion of Short-Time Fourier Transform and timbre Features

نویسندگان [English]

  • V Bagheri 1
  • A Keshavarz 2
  • H Rostami 3

2 Persian Gulf University Faculity

چکیده [English]

Detection and classification of Marine vessels based on their acoustic radiated noise is an important part of sonar systems. I this paper passive sonar targets classification algorithms is reviewed and a new algorithm is proposed. LDA feature extraction algorithm and Fusion of short time Fourier and timbre features is used in proposed algorithm which is called STFTLDA-Timb. Extracted features of proposed algorithm, are highly discriminant and classification accuracy of proposed algorithm is 8.45% better than STFT based classification algorithm. Obtained results of real data passive sonar classification show that classification accuracy of proposed algorithm is better than some common classification algorithms like statistical classifiers, neural networks and Ensemble Learning algorithms.

کلیدواژه‌ها [English]

  • sonar
  • passive
  • Classification
  • timbre
  • Fusion

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