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LWS-Based Time-Domain Synthetic Algorithm with Constant Amplitude in Radar Transmit Waveform

机译:基于LWS的时域综合算法,雷达中恒定幅度发射波形

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摘要

As the working electromagnetic environment of radar is becoming more and more complex, the research on single-target problem can no longer meet the actual needs. Therefore, this paper changes single-target problem into multitarget problem based on the traditional water-filling method. In order to better meet the actual environment and requirement, this paper proposes a new algorithm with phase factor added based on the general water-filling algorithm. A time-domain synthetic algorithm based on the linear weighted summation (LWS) method is proposed. The minimum mean square error (MMSE) is used to measure the proximity between the radar multitarget optimal transmit waveform algorithm and the time-domain synthetic algorithm. The MMSE-based cost function is a nonlinear least square error estimation problem, and the time-domain waveform can be obtained after solving it. Simulation results show that the energy spectrum density (ESD) of the synthetic signal after adding the phase is very close to the optimal energy spectrum density of LWS algorithm in three cases. The time-domain synthetic algorithm based on signal-to-interference-plus-noise ratio (SINR) has better detection and recognition performance than that based on mutual information (MI).
机译:随着雷达的工作电磁环境变得越来越复杂,对单目标问题的研究无法符合实际需求。因此,本文基于传统的水灌装方法将单目标问题变为多元问题。为了更好地满足实际环境和要求,本文提出了一种基于普通水填充算法添加了相位因子的新算法。提出了一种基于线性加权求和(LWS)方法的时域合成算法。最小均方误差(MMSE)用于测量雷达多元靶优化发射波形算法与时域合成算法之间的接近度。基于MMSE的成本函数是非线性最小二乘误差估计问题,并且可以在求解之后获得时域波形。仿真结果表明,在三种情况下,添加相位后,合成信号的能谱密度(ESD)非常接近LWS算法的最佳能谱密度。基于信号到干扰 - 加噪声比(SINR)的时域合成算法具有比基于互信息(MI)的检测和识别性能更好。

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