کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6957357 | 1451916 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Low-complexity adaptive broadband beamforming based on the non-uniform decomposition method
ترجمه فارسی عنوان
پرتو فرابنفش پهنای باند سازگار با کمبود پیچیدگی بر اساس روش تجزیه غیر یکنواخت
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کلمات کلیدی
پرتوهای باند پهن پرتو فریم سازگار با زیرباند، روش تجزیه یکنواخت، تجزیه غیر یکنواخت،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Sub-band adaptive processing is an established method to design a broadband beamformer. The uniform decomposition method (UDM) is a common approach for designing sub-band adaptive beamformer (SAB) that would split the received signal into a number of uniform sub-bands. However, the UDM has redundancies on decomposed sub-bands at high frequencies in the passband. In this paper, we propose a number of techniques to overcome this issue. By proposing a novel relative bandwidth method (RBM), we obtain that the relative bandwidth of each sub-band is the same. Using this as a basis, we present a non-uniform decomposition method (NUDM) such that the NUDM has fewer sub-bands than the conventional UDM, leading to reduced computational complexity. We also propose an elegant metric, adjacent bandwidth ratio (ABR), to facilitate easier comparison of non-uniformity. We then extend NUDM method to provide a fast variant of the non-uniform decomposition SAB (FNUD-SAB). We ensure that the sub-band frequencies and corresponding adaptive weights are available as part of the proposed FNUD-SAB method. With undistorted response to the desired signal and effective anti-jamming capability, the new beamformer reduces the computational complexity by reducing the number of sub-bands. Simulation results highlight the effectiveness of the proposed methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 151, October 2018, Pages 66-75
Journal: Signal Processing - Volume 151, October 2018, Pages 66-75
نویسندگان
Shurui Zhang, Jeyarajan Thiyagalingam, Weixing Sheng, Thia Kirubarajan, Xiaofeng Ma,