ID 原文 译文
26725 该方法首先对SAR图像进行分割预处理，得到目标区图像数据；然后基于BCS模型，根据训练样本构造传感矩阵；求解测试样本相应的稀疏系数矢量，根据稀疏系数矢量中对应训练样本类别元素的L2范数判定目标类型。 The method of SAR image segmentation preprocessing in the first place, get the target area image data;Then based on the BCS model, according to the training sample structure sensing matrix;To solve the test samples corresponding sparse coefficient vector, according to the sparse coefficient vectors in the corresponding training sample category elements of L2 norm to determine the target type.
26726 采用美国运动和静止目标获取与识别(movingand stationary target acquisition and recognition，MSTAR)计划公开发布的SAR目标数据库进行实验，结果表明该方法具有良好的识别效果。 By the American college of sports and stationary target acquisition and recognition (movingand stationary target acquisition and recognition, MSTAR) plan public release of SAR target database for experiments, the results show that the method has good recognition effect.
26727 在分析短时自相关法的基础上，探讨了使用谐波自相关方法进行基音频率提取。 On the basis of the analysis of short time autocorrelation method, discusses the harmonic autocorrelation method is used to extract pitch frequencies.
26728 首先根据语音信号建立谐波自相关模型，通过最小二乘法提取基音谐波频率。 First harmonic autocorrelation model is established according to the speech signal, by the least square method to extract the pitch harmonic frequency.
26729 然后根据基音谐波频率建立一个周期单位脉冲序列函数，用该函数加权短时自相关函数计算谐波数。 Then according to the pitch harmonic frequency function to establish a cycle unit impulse sequences, with the function weighted short-time autocorrelation function calculation of harmonic.
26730 最后利用提取的基音谐波和相应的谐波数目进行基音频率估计。 Finally using the extracted pitch harmonic and harmonic number of the corresponding pitch frequency estimation.
26731 实验表明在较低信噪比时，谐波自相关法基音检测错误率为5.0%，比自相关法降低了13.6%。 Experiments show that in low signal-to-noise ratio, harmonic autocorrelation/sound detection error rate is 5. 0%, than the autocorrelation method was reduced by 13. 6%.
26732 研究无人作战飞机(unmanned combat aerial vehicle，UCAV)对地攻击阶段轨迹规划问题。 The unmanned combat aircraft (unmanned combat aerial vehicle, UCAV) ground attack phase trajectory planning problems.
26733 首先，在综合UCAV的气动力特性、发动机推力特性基础上建立UCAV质点模型和动力学模型，并结合UCAV平台初始条件、机动性以及武器投射条件构建约束条件； First of all, on the aerodynamic characteristics of a comprehensive UCAV, engine thrust characteristics of UCAV established on the basis of particle model and dynamics model, and combining the UCAV platform initial condition, the mobility and weapons project build constraint conditions;
26734 针对当前轨迹规划中没有考虑雷达散射截面(radar cross section，RCS)随UCAV姿态角改变而动态变化这一缺陷，建立综合考虑动态RCS的威胁概率和攻击时间的目标函数； Based on the analysis did not consider the radar scattering cross section in the trajectory planning (radar cross section, the RCS) with the UCAV attitude Angle change and dynamic changes of this defect, establish comprehensive considering dynamic RCS probability and the threat of attack time of the objective function;