ID 原文 译文
55847 建立双重语言信息的结构转化方法,提出了基于综合偏好矩阵的方案整体绩效测度方法;以专家判断矩阵和方案综合偏好矩阵的偏离度为控制变量,构建了辨别弱有效性专家的目标规划模型;通过将专家意见表征为多维空间向量,建立了弱有效性专家意见的修正方法及修正步长优化模型,进而提出了双重信息的决策方法。 The structure of the dual language information transformation method, is proposed based on comprehensive preference matrix solution to measure the overall performance;To the overall preference matrix of expert judgment matrix and deviation as control variables, build the effectiveness to identify weak expert goal programming model;By experts to characterization of multidimensional space vector, a weak validity of expert opinion correction method is established and fixed step length optimization model, and then puts forward the decision method of dual information.
55848 提出了一种基于到达时间(time of arrival,TOA)和到达时间差(time difference of arrival,TDOA)的空中运动平台对目标高精度三维定位的无源定位方法。 Is put forward based on the arrival time (the time of arrivals from TOA) and arrival time (the time difference of concatenated, TDOA) of airborne platform to target high precision three-dimensional positioning method of passive location.
55849 该方法使用3个辅站信号到空中运动平台的TOA以及辅站位置确定空中运动平台自身的位置,然后依据目标散射回波到达各个辅站与空中运动平台的TDOA确定目标的位置。 The method USES three auxiliary signal to airborne platform of TOA and auxiliary stand location to determine the location of the airborne platform itself, then on the basis of target scattering echo to each auxiliary station and air movement platform TDOA to determine the location of the object.
55850 分析了三维TDOA目标定位模糊产生的原因,提出了一种无模糊的高精度TDOA目标位置求解算法。 3 d TDOA location is analyzed the causes of fuzzy, this paper proposes a high precision without the fuzzy goal TDOA location algorithm.
55851 仿真结果表明,该算法比经典的TDOA定位算法精度高,而且不存在定位模糊,从而验证了该空中运动平台对目标进行无源定位方法的有效性以及正确性。 Simulation results show that the proposed algorithm outperforms the classical TDOA localization algorithm accuracy is high, and there is no positioning fuzzy, confirming the air movement platform to target passive location method is effective and correct.
55852 为了提高联合网络编码调制在多址接入中继系统的上行链路衰落信道下的性能,提出了在中继节点处使用卷积码与16进制正交幅度调制改进集分割映射星座映射方式相匹配的联合编码调制方式,并在基站处设计了相应的迭代译码解调方案。 In order to improve the joint network coding modulation in multiple access repeater uplink fading channel, the performance of the system, puts forward the relay node using convolution code and hexadecimal quadrature amplitude modulation to improve the way of mapping the constellation set segmentation matching joint coded modulation method, and at the base station design the corresponding iterative decoding demodulation scheme.
55853 通过衰落信道下系统误比特率的性能渐近限和外信息转移图的分析,证明了在衰落信道下,改进集分割映射在卷积码迭代译码方案下优于传统格雷映射方式。 Through the fading channel bit error rate performance of the system asymptotic limit and the external information transfer diagram analysis, proves that under the fading channel, the improved set segmentation map under convolution code iterative decoding scheme is superior to the traditional gray mapping method.
55854 软件仿真结果也证明了在瑞利衰落信道下,改进集分割映射相对于传统格雷映射方法在误码率为10-5时获得了4dB的显著性能增益。 Software simulation results also proved under Rayleigh fading channel, the improved set partitioning map is compared with the traditional gray mapping method when the bit error rate is 10-5 won a significant performance gain 4 db.
55855 为了进一步提高图像配准的运算效率、匹配正确率及配准精度,提出了一种利用双树复小波变换和加速鲁棒特征(speeded up robust features,SURF)的图像配准算法。 In order to further improve the operation efficiency, matching accuracy of image registration and registration accuracy, this paper proposes a using dual tree complex wavelet transform and accelerate the robust features (speeded up robust features, SURF) image registration algorithm.
55856 首先利用双树复小波变换将参考图像和待配准图像分解为低频部分和高频部分,选取其对应的低频部分作为SURF算法的输入图像,得到两者的粗匹配结果;然后通过随机抽样一致(random sample consensus,RANSAC)算法对粗匹配点对进行提纯,剔除误匹配点对,解决了SURF算法存在较多错误匹配点对的问题,同时计算出最佳匹配的变换模型参数;最后根据该变换模型参数对待配准图像进行几何变换,经双线性插值确定灰度,完成图像的配准。 Firstly, the dual tree complex wavelet transform is used to change the reference image and stay registration image is decomposed into low frequency part and high frequency part, select the corresponding low frequency part of the input image, the SURF algorithm for both coarse matching results;And then through the random sample consensus (the random sample consensus, RANSAC) algorithm for purification of coarse matching point pairs, to eliminate false match point, solve the problems more error matching point to SURF algorithm, to calculate the best match of transformation model parameters at the same time;Finally, according to the transformation model parameters with registration image geometry transform, the bilinear interpolation to determine grey, finish the image registration.