IJE TRANSACTIONS C: Aspects Vol. 31, No. 6 (June 2018) 916-920   

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M. Kafi, J. Ranjbar, J. Khalilpour and S. Zarezade
( Received: August 22, 2017 – Accepted in Revised Form: January 04, 2018 )

Abstract    In this paper a novel method for detecting targets in inactive radars is presented. In this method, the time history of cellsof the ambiguity function is used for detection. For this purpose, the cell history is considered as a random field. Then, using adaptive filter, the string time of the desired target are separated from the string time of noise and clusters in the environment. In order to evaluate the performance of the proposed method for an environment including three targets with simulated different distances and speeds, the results were compared with the other two methods at the same conditions. Based on the results obtained, this method has the ability to detect targets for SCNRs of up to -10 dB for all three values of the probability of false alarms. The obtained results also showed the superiority of the proposed method compared to other alternatives in such manner. Accordingly, the probability of detection for the proposed method at least 12.5 percent better than ACM and 8 percent better than NNTD. It also shows that for SCNRs larger than zero dB, this method has a 100% detection capability.


Keywords    Bistatic passive Radar, Ambiguity Function, Delay, Doppler, Noise


چکیده    در این مقاله یک روش جدید به منظور شناسایی و آشکارسازی اهداف در رادارهای غیر فعال ارائه شده است. در این روش از سابقه زمانی سلول های تابع ابهام برای آشکارسازی استفاده شده است. برای این منظور ابتدا سابقه زمانی سلول ها به صورت یک رشته تصادفی در نظر گرفته می شود. سپس با استفاده از یک فیلتر وفقی رشته های زمانی مربوط به اهداف مورد نظر از رشته های زمانی مربوط به نویز و کلاتر موجود در محیط جدا می شود. به منظور بررسی عملکرد روش پیشنهادی برای محیطی شامل 3 هدف با فواصل و سرعت های متفاوت شبیه سازی و نتایج حاصل از آن با دو روش دیگر در شرایط یکسان مقایسه شده است. نتایج بدست آمده نشان می دهد این روش از نظر درصد آشکار سازی در حدود 5/12 درصد نسبت به دیگر روش ACM و در حدود 8 درصد نسبت به روش NNTD عملکرد بهتری دارد.


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