Cognitive radar can overcome the shortcomings of traditional radars that are difficult to adapt to complex environments and adaptively adjust the transmitted waveform through closed-loop feedback. The optimization design of the transmitted waveform is a very important issue in the research of cognitive radar. Most of the previous studies on waveform design assume that the prior information of the target spectrum is completely known, but actually the target in the real scene is uncertain. In order to simulate this situation, this paper uses a robust waveform design scheme based on signal-to-interference-plus-noise ratio (SINR) and mutual information (MI). After setting up the signal model, the SINR and MI between target and echo are derived based on the information theory, and robust models for MI and SINR are established. Next, the MI and SINR are maximized by using the maximum marginal allocation (MMA) algorithm and the water-filling method which is improved by bisection algorithm. Simulation results show that, under the most unfavorable conditions, the robust transmitted waveform has better performance than other waveforms in the improvement degree of SINR and MI. By comparing the robust transmitted waveform based on SINR criterion and MI criterion, the influence on the variation trend of SINR and MI is explored, and the range of critical value of T_y is found. The longer the echo observation time is, the better the performance of the SINR-based transmitted waveform over the MI-based transmitted waveform is. For the mutual information between the target and the echo, the performance of the MMA algorithm is better than the improved water-filling algorithm.

中文翻译：

---

基于二等分和最大边际分配方法的信息熵鲁棒波形设计

认知雷达可以克服传统雷达难以适应复杂环境的缺点，并且可以通过闭环反馈来自适应地调整发射波形。发射波形的优化设计是认知雷达研究中非常重要的问题。以前的大多数波形设计研究都假定目标频谱的先验信息是完全已知的，但实际上，真实场景中的目标是不确定的。为了模拟这种情况，本文采用了一种基于信噪比（SINR）和互信息（MI）的鲁棒波形设计方案。建立信号模型后，根据信息论推导目标和回波之间的SINR和MI，并建立了MI和SINR的鲁棒模型。下一个，通过使用最大边际分配（MMA）算法和对分算法改进的注水方法，可以最大化MI和SINR。仿真结果表明，在最不利的条件下，鲁棒的传输波形在SINR和MI的改善程度上具有优于其他波形的性能。通过比较基于SINR准则和MI准则的鲁棒传输波形，探讨了对SINR和MI的变化趋势的影响，并确定了临界值的范围。T _y被找到。回波观察时间越长，基于SINR的传输波形的性能就优于基于MI的传输波形。对于目标和回波之间的相互信息，MMA算法的性能优于改进的注水算法。