基于先验知识的自适应检测波形设计

研究了基于先验知识的认知雷达自适应检测波形设计问题，推导了发射波形对于检测性能影响的闭式解并提出了一种基于交替投影法的波形优化算法。算法根据所推导出的检测概率与发射波形、接收机滤波器之间关系的闭式表达式，通过联合优化发射波形和接收机滤波器，达到提高接收机的检测概率和降低信号相关杂波负面影响的目的。分析仿真结果可知，所设计波形的检测性能优于传统的恒包络LFM波形。当采用多组初始波形进行迭代优化时，检测概率趋向于相同值，这表明该算法的收敛性良好。

Adaptive detection waveform design based on prior knowledge

In the presence of prior knowledge, the problem of detecting waveform design for cognitive radar is studied. The closed form of the influence of emission waveform on target detection is derived, and the waveform optimization algorithm based on alternating projection method is proposed. In order to improve the detecting performance of cognitive radar and reduce the negative impact of the signal-dependent clutter, the paper optimizes the transmitted waveform and the receiver filter jointly based on the derived closed-form solution of the relationship between the detection probability and the transmitted waveform. The simulation results indicate that the detection performance of the designed waveform is better than that of the constant envelope signal LFM waveform which is used widely in traditional radar. When it uses different initial waveforms to solve the optimization problem, the probability of detection after several iterations will approach the same value, which indicates that the convergence of the algorithm is good.