کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6951833 | 1451705 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Adaptive waveform selection for maneuvering target tracking in cognitive radar
ترجمه فارسی عنوان
انتخاب شکل موج سازگار برای مانور ردیابی هدف در رادار شناختی
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Cognitive radar can adjust the transmitted waveform adaptively to the external dynamic environment for a better target tracking performance than the traditional radar transmitting the fixed waveform. There are two key problems in the tracking system of cognitive radar, which are how to build the transmitted waveform library and how to select the optimal waveform for target tracking in the waveform library. The problem of adaptive waveform selection for maneuvering target tracking is studied in this paper. The factors influencing the target tracking accuracy are analyzed, and the maneuvering target tracking framework in cognitive radar is proposed. Considering that the narrow pulses correspond to good delay but poor Doppler resolution capability and that the long constant-frequency pulses have the opposite behavior, we build a transmitted waveform library consisting of the waveforms with both types of properties using the fractional Fourier transform (FrFT) technique. And the criteria for waveform selection in the control theoretic and information theoretic approaches are discussed in detail. The corresponding solutions of waveform selection in the waveform library are given, respectively. The superior performance of the adaptive waveform over the fixed waveform is illustrated with simulation examples. The simulations demonstrate that the target tracking algorithm is also very important for waveform selection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 75, April 2018, Pages 210-221
Journal: Digital Signal Processing - Volume 75, April 2018, Pages 210-221
نویسندگان
Biao Jin, Jiao Guo, Baofeng Su, Dongjian He, Zuojing Zhang,