Block Least Mean Squares processing of noise radar waveforms

M. Meller, S. Tujaka
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引用次数: 8

Abstract

Noise radars usually employ correlation processing of waveforms. However, vulnerability to clutter is a serious disadvantage of this approach. This paper considers using Least Squares (LS) based methods. In particular, highly efficient Block Least Mean Squares (Block LMS) algorithm is studied in details. The formula for integration gain of Block LMS is derived. Compared to analogue quantity for correlation processing, it shows significant advantage of the proposed solution in terms of robustness to clutter. The Doppler response of the algorithm is analyzed, which - under proper choice of algorithm parameters - is identical to that of correlation approach. Simulation experiments confirm that when heavy clutter is present, the proposed method outperforms correlation processing significantly.
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噪声雷达波形的块最小均二乘处理
噪声雷达通常采用波形相关处理。然而,易受杂乱的影响是这种方法的一个严重缺点。本文考虑使用基于最小二乘的方法。重点研究了高效的块最小均方差(Block LMS)算法。推导了块LMS的积分增益公式。与相关处理的模拟量相比,该方法在对杂波的鲁棒性方面具有显著优势。分析了该算法的多普勒响应,在适当选择算法参数的情况下,算法的多普勒响应与相关方法的多普勒响应相同。仿真实验表明,在杂波较重的情况下,该方法明显优于相关处理。
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