تشخیص اهداف راداری با استفاده از شبکه عصبی عمیق GMDH

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی برق جنگ الکترونیک دانشگاه هوایی شهید ستاری

2 دانشجوی دکتری مهندسی برق جنگ الکترونیک دانشگاه جامع امام حسین(ع)،

3 دانشیار، دانشگاه جامع امام حسین(ع)

چکیده

رادار وسیله الکترومغناطیسی است که برای تشخیص و تعیین موقعیت هدف‌‌ها به‌کار می‌‌رود. اساسی­ترین وظیفه رادار استخراج اطلاعات در مورد هدف، به­وسیله اندازه­گیری مشخصات میدان الکترومغناطیسی امواج بازگشتی از هدف است. محیط راداری هر کشور جزو محدوده‌‌های امنیتی و راهبردی هر کشور می‌‌باشد. حفظ امنیت این محیط و شناسایی اهداف موجود در آن می‌‌تواند یکی از الزامات مهم محسوب گردد. در تشخیص اهداف راداری چالش‌ها و مشکلاتی همچون عدم دقت، صحت تشخیص و خطای بالا مطرح می‌‌باشد. روش‌‌های مختلفی تاکنون از جمله روش‌های مبتنی بر فرکانس­های تشدید طبیعی هدف، پلاریزاسیون سیگنال بازگشتی، روش­های یادگیری ماشین و غیره به‌منظور تشخیص اهداف راداری مطرح شده است. با وجود کاربردهای فراوانی که این روش‌ها داشته‌اند، اما هنوز نتوانسته‌اند چالش‌‌های موجود در رادار را برطرف نمایند. از این‌رو، در این مقاله با به‌کارگیری الگوریتم یادگیری عمیق GMDH اقدام به تشخیص اهداف راداری نموده­ایم. با شبیه‌سازی روش پیشنهادی و مقایسه آن با سایر روش­هایی همچون (RIN, SAE, SCAE, SDAE, CNN, LSVM, K-SVD)، به‌طور میانگین 5 درصد بهبود حاصل شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying Radar Targets using the GMDH Deep Neural Network

نویسندگان [English]

  • saeed Talati 1
  • milad akbari sani 2
  • MohammadReza Hassani Ahangar 3
1 PhD student of Electronic Warfare Shahid Sattari University of Medical Sciences
2 PhD student of Electronic Warfare, Imam Hossein University,Email
3 Associate Professor, Imam Hossein University
چکیده [English]

Radar is an electromagnetic device used to detect and determine the position of targets. The most basic task of radar is to extract information about the target by measuring the electromagnetic field characteristics of the return waves from the target. The radar environment of each country is one of the security and strategic areas of each country. Maintaining the security of this environment and identifying its goals can be one of the important requirements. Challenges and problems such as inaccuracy and inaccuracy of detection and high error are raised in the detection of radar targets. Various methods have been proposed so far, such as techniques based on target natural intensification frequencies, reversible signal polarization, machine learning methods, etc., to detect radar targets. Despite the many uses of these methods, they have not yet been able to meet the challenges of radar.  Therefore, in this paper, we have identified radar targets using the GMDH Deep Learning Algorithm. By simulating the proposed method and comparing it with other methods such as RIN, SAE, SCAE, SDAE, CNN, LSVM, K-SVD, the average has improved by 5%.

کلیدواژه‌ها [English]

  • Clustering
  • Radar Targets
  • Deep Learning GMDH
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