کاهش نرخ نمونه‌برداری و بهبود عملکرد سیستمیِ رادار FMCW با استفاده از تکنیک حسگری فشرده دوگانه

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه صنعتی شیراز

چکیده

بنا به تئوری حسگری فشرده اگر سیگنالی قابلیت نمایش تُنُک در فضایی مناسب را داشته باشد می‌توان با استفاده از روش‌های بهینه‌سازی، بازسازی دقیق سیگنال را از روی مشاهداتی به مراتب کمتر از آنچه که تئوری شانون لازم می‌داند انجام داد. وجه تمایز سیگنال از نویز، همین قابلیت نمایش تنک برای سیگنال و عدم این ویژگی برای نویز است و از طرف دیگر، یافتن جواب در حسگری فشرده منوط به یافتن تنک‌ترین جواب است؛ بنابراین با این تکنیک می‌توان سیگنالِ تمیز را از نویز جدا کرد. در رادار FMCW فاصله اهداف از روی فرکانس سیگنال خروجی گیرنده به‌دست می‌آید. از آنجایی که این سیگنال در حوزه فرکانس نمایشی تنک دارد بنابر نظریه حسگری فشرده، می‌توان با تعداد کمی از داده‌ها، آن را به طور مطلوب بازسازی کرد. همچنین در این مقاله با ارائه روش جدیدی برای پردازش سیگنال در رادار FMCW مبتنی بر حسگری فشرده، نشان داده می‌شود که می‌توان اثر نویز در سیگنال خروجی گیرنده را کاهش و عملکرد سیستمیِ ‌رادار را بهبود داد.

کلیدواژه‌ها

عنوان مقاله [English]

Sampling Rate Reduction and System Performance Improvement of FMCW Radar Using Dual Compressed Sensing Technique

نویسندگان [English]

  • Mostafa Mozaffari
  • Sadegh Samadi
چکیده [English]

Based on the compressed sensing theory, if a signal is sparse in a suitable space, by using the
optimization methods, signal could be accurately reconstructed from measurements that are
significantly less than the theoretical Shannon requirements. The sparse representation may exist
for the signal and it is not available for the noise; this could be used to distinguish these two. On
the other hand, in compressed sensing, finding the answer hinges on finding the most sparse
solution; thus this technique can separate clean signal from the noise. In FMCW radar, the
distance of a target could be obtained from the frequency of the receiver output signal. Since this
signal has a sparse representation in the frequency domain, based on compressed sensing theory,
it could be reconstructed from a few number of data. In this paper, a new method for signal
processing of FMCW radar is presented based on compressed sensing. Moreover, by
considering noise removal feature that is in the nature of this technique, it is shown that the
effect of noise on the receiver output signal can be reduced and the system performance of the
radar can be improved.

کلیدواژه‌ها [English]

  • Compressed Sensing
  • FMCW Radar
  • Noise Removal
  • Sampling
  • Sparse Representation

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سابقه مقاله

  • تاریخ دریافت: 09 شهریور 1394
  • تاریخ بازنگری: 02 بهمن 1402
  • تاریخ پذیرش: 28 شهریور 1397

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