时间分辨力约束下目标检测的波形优化设计

以最大化检测概率为优化准则，采用基于凸优化和随机化方法的具有相似性约束的相位编码算法（Phase Coding Algorithm with Similarity Constrain，PCA-SC）来设计发射波形，解决了主动声呐系统增大探测目标发射功率却不能提高检测概率的问题。同时，为有效降低PCA-SC算法所设计编码自相关函数的整体旁瓣级，提高其检测微弱目标的能力，在PCA-SC算法的基础上，结合新循环算法（Cyclic Algorithm-New，CAN）多相编码技术，提出了基于CAN的PCA-SC波形优化方法（Cyclic algorithm-new Phase Coding Algorithm with Similarity Constrain，CAN-PCA-SC）。仿真实验结果表明，PCA-SC和CAN-PCA-SC两种波形优化方法获得的发射信号均能够在满足系统所需时域分辨能力的要求下，实现检测概率的最大化，提高了目标检测性能，将时域分辨能力和检测性能有效地统一起来。相比PCA-SC波形设计方法，CAN-PCA-SC波形设计方法在保证获得的发射信号的检测概率优化效果一致的情况下，具有更低的积累旁瓣水平和更好的检测微弱目标的能力。

Waveform optimization design of target detection under the constraint of time resolution

The PCA-SC (Phase Coding Algorithm with Similarity Constrain) algorithm based on convex optimization and randomization is proposed for transmitting signal design, which can improve the detection performance of active sonar for target parameter estimation in the presence of clutter. Furthermore, in order to detect weak targets, a new Cyclic Algorithm-New (CAN) based PCA-SC algorithm (termed as CAN-PCA-SC algorithm) is proposed. Through theoretical analyses and numerical simulations, it is shown that the signals designed by the two algorithms can maximize the detection probability while satisfying the requirement of time resolution, so that the performances of sonar detection and target parameter estimation are improved. Compared with PCA-SC algorithm, the CAN-PCA-SC algorithm has the capability of lower accumulated sidelobe level and better performance of detecting weak target under the condition that the detection probability optimization effect of the obtained transmitting signal is consistent.