A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex ...A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization. Tests using experimental data show that, compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR), the proposed algorithm yields better results with less computation work.展开更多
针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资...针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资源,使得飞机编队对组网雷达系统的协同干扰效能始终保持最优。首先,根据雷达网不同的工作状态和信息融合规则,构建基于检测概率和瞄准概率的双因子干扰效能评估函数,然后考虑干扰资源约束建立关于目标选择和功率分配的双变量非凸优化模型,并基于此提出了一种结合改进布谷鸟搜索(improved cuckoo search,ICS)算法与KKT(Karush-Kuhn-Tucker,KKT)优化条件的求解方法。最后,仿真结果证明了所提联合资源自适应调度策略的有效性。展开更多
基金Supported by the Hi-Tech Research and Development Program of China (No. 2011AA120102)
文摘A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization. Tests using experimental data show that, compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR), the proposed algorithm yields better results with less computation work.
基金supported by National Basic Research Program of China (973 Program)(No.2012CB215102)National Natural Science Foundation of China(No.51206138)China Southern Power Grid Project(No.K-ZD2012-003)
文摘针对飞机编队协同干扰组网雷达系统的资源分配问题,提出了一种联合目标选择与功率分配的自适应调度(adaptive scheduling method of joint target selection and power allocation,JTAPM)方法,其核心是通过实时调度干扰机的波束和功率资源,使得飞机编队对组网雷达系统的协同干扰效能始终保持最优。首先,根据雷达网不同的工作状态和信息融合规则,构建基于检测概率和瞄准概率的双因子干扰效能评估函数,然后考虑干扰资源约束建立关于目标选择和功率分配的双变量非凸优化模型,并基于此提出了一种结合改进布谷鸟搜索(improved cuckoo search,ICS)算法与KKT(Karush-Kuhn-Tucker,KKT)优化条件的求解方法。最后,仿真结果证明了所提联合资源自适应调度策略的有效性。
