کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
380821 1437453 2013 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Development and performance evaluation of an improved complex valued radar pulse compressor
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Development and performance evaluation of an improved complex valued radar pulse compressor
چکیده انگلیسی

Pulse compression is an important and burning issue in radar signal processing. In the recent past, many adaptive and neural network based methods have been proposed to achieve effective pulse compression performance for real coded transmitted waveforms. Even though the radar signal is complex, it is mostly processed as real-valued in-phase and quadrature components. Hence it is desirable that for processing complex radar signal for pulse compression both the structure as well as the learning algorithm associated with it need to be complex in nature. Accordingly in this paper a novel adaptive method is proposed by employing a complex valued fully connected cascaded (CFCC) neural network. For training this network, a new complex Levenberg–Marquardt (CLM) algorithm is derived and used for imparting effective training of its weights. The new CLM based CFCC (CFCC-CLM) model offers superior convergence performance with the least residual mean squared error during training phase compared to those provided by the multilayer perceptron (MLP) trained with complex domain backpropagation (CDBP) and CLM based methods. Further the comparison of peak signal-to-sidelobe ratio (PSR) under noisy and Doppler shift conditions of the proposed method exhibits best performance compared to those offered by the MLP-CDBP, MLP-CLM and the matched filter (MF) based methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 26, Issue 10, November 2013, Pages 2653–2660
نویسندگان
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