ID 原文 译文
8054 改进PASTd算法首先给出了目标角度自动关联算法,且能够实现收发角度的自动配对。 PASTd algorithm firstly gives the target Angle automatic correlation algorithm, and can realize automatic matching of sending and receiving Angle.
8055 然后利用估计出的收发角度,得到此时的收发联合导向矢量。 Then, estimate the sending and receiving Angle, are used to get the transceiver joint direction vector at this time.
8056 最后用收发联合导向矢量更新PASTd算法估计出的特征矢量,作为下一时刻跟踪算法的初始矢量。 Finally with transceiver joint orientation vector update PASTd algorithm to estimate the characteristic vector, as the initial vector of the algorithm of the next moment.
8057 改进算法克服了PASTd算法的不足,能够成功跟踪相同角度的目标,并且实现了目标收发角度自动配对和关联。 Improved algorithm to overcome the deficiency of the PASTd algorithm can successfully track the targets with the same Angle, and achieve the transceiver automatic matching Angle and associations.
8058 仿真结果验证了理论分析的有效性。 The simulation results verify the validity of the theoretical analysis.
8059 针对不同工作环境的机载设备故障概率预测问题,提出自适应权重的插值-拟合-迁移学习(interpolation-fitting-transfer learning,ITF)算法。 According to different work environment of the airborne equipment failure probability prediction problem, put forward the adaptive weighting interpolation fitting - migration study (interpolation fitting - transfer learning, ITF) algorithm.
8060 算法根据数据量和数据特征(分布相似度和信息熵)对插值、拟合、迁移学习赋予一定的权重进行线性组合。 Algorithm according to the amount of data and data characteristics (distribution similarity and entropy) for interpolation, fitting and linear combination migration study gives some weights.
8061 插值和拟合方法可以对故障频率进行平滑,而迁移学习可以规避数据贫化所引起的预测风险。 Interpolation and fitting method can smooth the failure frequency, and the migration study can hedge the risks caused by data dilution prediction.
8062 分析该方法的可行性,通过仿真实例展示算法在预测准确度上的优势,并讨论算法中仍待解决的问题和下一步的工作。 Analysis the feasibility of this method, the simulation example shows the algorithm on the prediction accuracy of advantage, and discuss the algorithm still to be solved in question and the next step of work.
8063 针对非线性系统状态估计中,平滑变结构滤波(smoothing variable structure filter,SVSF)算法要求系统是连续可微的且需要计算系统Jacoby矩阵的问题,提出了基于球面径向基容积规则的平滑变结构滤波(cubature-smoothing variable structure filter,C-SVSF)算法,该算法避免了对非线性系统Jacoby矩阵的计算; State estimation of nonlinear system, a smooth variable structure filter (smoothing variable structure filter, SVSF) algorithms require system is continuously differentiable and Jacoby matrix problem, need to compute system is presented based on the spherical radial basis (volume smooth variable structure filtering rules (cubature - smoothing variable structure filter, C - SVSF) algorithm, the algorithm avoids the Jacoby matrix calculation for nonlinear system;