ID 原文 译文
20085 最后完成载机偏航下风场速度的准确估计。 Finally, theaccurate estimation of the wind speed under the aircraft yawing is got.
20086 仿真结果验证了该方法能够在载机偏航情况下，获得风场速度的有效估计。 The simulation results show that the proposed method can obtain an effective estimation of wind speed under aircraft yawing.
20087 基于宽带电力线通信(PLC)中，高斯分布的背景噪声往往不能如实反应人类日常用电活动产生的噪声特性， In broadband Power-Line Communications (PLC), the background noise commonly assumed as Gaussian may not truly depict the effect of the human activities on noise characteristics.
20088 为此，该文提出用对称 稳定(S S)分布对PLC背景噪声进行建模，研究基于正交频分复用(OFDM)系统误符号率(SER)的解析性能，并指出在S S背景噪声的情况下，对接收到的复基带S S噪声样值进行快速傅里叶变换(FFT)后，信号的实部和虚部仍然服从单变量的S S分布， Symmetric Alpha-Stable (S S) process is used to model the PLC background noise, obtaining analytical expressions, and the analytical Symbol Error Rate (SER) performance is investigated for Orthogonal Frequency Division Multiplexing (OFDM)-based PLC systems. The analysis shows that the real or the imaginary component afterthe Fast Fourier Transform (FFT) of the received complex baseband S S noise samples follows univariate S Sdistribution.
20089 且由于S S背景噪声占用了整个OFDM系统的频带，系统的误符号率性能随着FFT点数增加而产生恶化。 Due to the fact that the S S background noise occupies the whole OFDM system bandwidth, theSER performance of the system decreases as the employed FFT size grows.
20090 在压缩感知成像算法中，真实目标点一般不会恰好落在预先划定的网格点上， In Compressive Sensing (CS) imaging algorithms, the true targets usually can not locate on the pre-defined grids exactly.
20091 这种网格偏离(Off-grid)问题会带来真实回波与测量矩阵之间的失配，严重降低雷达成像的性能。 Such Off-grid problems result in mismatch between true echo and measurement matrix,which seriously degrades the performance of radar imaging.
20092 针对多输入多输出(MIMO)雷达3维成像的网格失配问题，该文提出一种自适应的Off-grid校正方法，基于Off-grid目标的稀疏回波模型构造贝叶斯概率密度函数，采用最大后验概率(MAP)方法求解含有失配偏差的稀疏像。 An adaptive calibration method is proposed to solvethe off-grid problems in MIMO radar Three-Dimensional (3D) imaging. Bayesian probability density functionscan be constructed based on the sparse echo model of Off-grid targets, and the Maximum A Posteriori (MAP)method is used to obtain sparse imaging with mismatch errors.
20093 与传统方法相比，该方法可以充分利用失配参数的先验信息，自适应地更新参数，降低了失配误差的影响，并能实现对稀疏目标和噪声功率的高精度估计。 Compared with the traditional methods, the proposed method can make full use of mismatch parameters’ priori information and adaptively update the parameters, which can reduce the influence of mismatch errors, and achieve high-precision estimation for sparse targets and noise power.
20094 仿真结果表明，该方法可以有效地实现对网格失配的优化，具有精确且稳定的成像性能。 Finally, the simulation results confirm that the proposed method can effectively optimize mismatch errors with accurate and stable imaging performance.