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首页> 外文期刊>Selected Topics in Signal Processing, IEEE Journal of >Optimizing Radar Waveform and Doppler Filter Bank via Generalized Fractional Programming
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Optimizing Radar Waveform and Doppler Filter Bank via Generalized Fractional Programming

机译:通过广义分数规划优化雷达波形和多普勒滤波器组

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摘要

Assuming unknown target Doppler shift, we focus on robust joint design of the transmit radar waveform and receive Doppler filter bank in the presence of signal-dependent interference. We consider the worst case signal-to-interference-plus-noise-ratio (SINR) at the output of the filter bank as the figure of merit to optimize under both a similarity and an energy constraint on the transmit signal. Based on a suitable reformulation of the original non-convex max-min optimization problem, we develop an optimization procedure which monotonically improves the worst-case SINR and converges to a stationary point. Each iteration of the algorithm, involves both a convex and a generalized fractional programming problem which can be globally solved via the generalized Dinkelbach’s procedure with a polynomial computational complexity. Finally, at the analysis stage, we assess the performance of the new technique versus some counterparts which are available in open literature.
机译:假设目标多普勒频移未知,我们将重点放在发射雷达波形的鲁棒联合设计和在存在信号相关干扰的情况下接收多普勒滤波器组。我们将滤波器组输出端的最坏情况下的信号干扰加噪声比(SINR)作为品质因数,以在发射信号的相似性和能量约束下进行优化。基于对原始非凸最大最小优化问题的适当重新表述,我们开发了一种优化程序,该程序可以单调地改善最坏情况下的SINR并收敛到固定点。该算法的每次迭代都涉及凸和广义分数规划问题,可以通过具有多项式计算复杂度的广义Dinkelbach程序来全局求解。最后,在分析阶段,我们将评估该新技术的性能,并与公开文献中提供的一些同类技术进行比较。

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