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).

中文翻译：

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雷达发射波形中基于LWS的恒定幅度时域合成算法

随着雷达工作电磁环境的日益复杂，单目标问题的研究已不能满足实际需求。因此，本文在传统的注水方法的基础上，将单目标问题转化为多目标问题。为了更好地满足实际环境和要求，在常规注水算法的基础上，提出了一种增加了相位因子的算法。提出了一种基于线性加权求和法的时域综合算法。最小均方误差（MMSE）用于测量雷达多目标最佳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，求解后可以得到时域波形。仿真结果表明，在三种情况下，相加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。基于信干噪比的时域综合算法比基于互信息的算法具有更好的检测和识别性能。