频谱拥挤环境中峰均功率比约束的认知雷达发射波形设计

复杂电磁环境的一个重要特征是频谱资源受限，合理使用有限的频谱资源是认知雷达发射波形设计必须考虑的问题。以峰值与平均功率比(PAR)为约束条件，设计认知雷达发射波形，最大化接收数据信噪比(SNR)，最小化波形频谱在受干扰频段内功率。该问题是二次约束的多目标优化问题，采用Pareto优化方法，将两个目标函数通过加权构成一个目标函数，从而构成一个二次约束二次规划非凸优化问题。进一步采用半定规划松弛和随机化方法，可以获得最优发射波形，其性能与Pareto加权系数和PAR约束条件等有关。计算机仿真分析表明，发射波形设计在SNR和干扰抑制能力方面存在制约关系，并可以通过增大发射机动态范围进一步改善性能。

Cognitive Radar Waveform Design with A Peak to Average Power Ration Constraint for Spectrally Dense Environments

The most important characteristic of the complex electromagnetic environment is the limitation of the radio frequency resource. As a result, the smart use of the limiting spectral resource is necessary to the waveform design for the cognitive radar. This paper designs the transmit waveform under the Peak to Average power Ratio (PAR), to maximize the Signal to Noise power Ratio (SNR) at the receiver, and simultaneously, minimize the power of the waveform in the interference frequency bands. The waveform design problem is a quadratically constrained multi-objective optimization problem. Exploiting the Pareto optimization method, the one objective function is obtained by weighted sum of the two ones, and the resultant problem reduces into a Quadratically Constrained Quadratic Program (QCQP). In order to solve it, the SemiDefinite Program (SDP) relaxation and randomization are used to achieve the optimal waveform, whose performance is related to the Pareto weights and the PAR constraint. The computer simulation results show that, there is a restrictive relationship between the SNR and interference suppression ability for the waveform design, and the performance can be improved by increasing the dynamic range of the transmitter.