ID 原文 译文
48526 针对以上问题,提出了一种基于不确定挠曲变形参数变化模型集的多模型滤波对准方案,以速度+姿态的匹配模式为例进行仿真分析。 To solve above problems, this paper proposes a model based on uncertain flexure deformation parameters set of multi-model filter alignment scheme, with the velocity + attitude matching model as an example for simulation analysis.
48527 结果表明,所提出的对准方法同基于单一模型的对准方法相比提高了对准精度和算法的环境适应性,是解决存在不确定挠曲变形干扰下的传递对准问题的一种有效方法。 Results show that the proposed alignment method compared with alignment method based on single model improves the alignment accuracy and adaptive algorithm of the environment, is to address the uncertainty flexure deformation transfer alignment problem under the interference of a kind of effective method.
48528 分析了非参数化谱估计方法,分析表明,它们所解决的优化问题都是加权最小二乘(weighted least square,WLS),不同在于如何估计广义噪声协方差矩阵来构建加权矩阵。 Non parametric spectrum estimation method is analyzed, the analysis shows that they solve the optimization problems are weighted least squares (weighted further square, WLS), different is how to estimate the generalized noise covariance matrix to construct weighted matrix.
48529 基于统一框架,提出了一种能同时估计信号频谱和观测噪声的自适应迭代非参数谱估计方法。 Based on a unified framework, this paper puts forward a kind of can at the same time as the signal spectrum and observation noise adaptive iterative nonparametric spectral estimation method.
48530 该方法在每一次迭代时都利用上一次估计结果来逐步逼近真实的广义噪声协方差矩阵。 The method in every iteration results estimated from the last time to gradually close to the real generalized noise covariance matrix.
48531 分析和仿真表明,本文方法具有分辨率高,谱泄漏抑制好,并能增强信号协方差矩阵的可逆性和频谱范围选择的随意性等特点。 Analysis and simulation show that the method has high resolution, good inhibition spectrum leakage, and can enhance the signal covariance matrix of the arbitrariness of reversibility and spectrum characteristics.
48532 针对多输入多输出(multiple-input multiple-output,MIMO)雷达反向投影(back projection,BP)成像算法运算量大、实时性差的问题,提出一种基于距离补偿和波束形成的高运算效率改进型MIMO雷达BP成像算法。 For multiple input multiple output (multiple input multiple output, MIMO) reverse projection (BP) back the projection, radar imaging algorithm computational complexity is big, the problem of poor real-time performance, put forward a kind of compensation and beamforming based on distance of high computation efficiency improved BP MIMO radar imaging algorithm.
48533 首先通过匹配滤波完成距离压缩和发射波形分离,然后在极坐标下对各个距离单元散射点的时延特性进行分析并简化,将传统BP算法中的延迟相加过程转化为波束形成过程,从而完成方位向聚焦。 First transmission waveform by matched filtering complete range compression and separation, and then under the polar coordinate time delay characteristics of scattering point all the distance units is analyzed and simplified, will delay in traditional BP algorithm combined into beamforming process, thus complete the orientation to focus.
48534 所提方法避免了对所有像素点逐个求时延,减小了运算量,并且便于数据的并行批量处理,极大地提高了运算效率。 Proposed method avoids the delay of all pixel points one by one, reduces the computational complexity, and easy to parallel batch processing of data, greatly improve the operation efficiency.
48535 仿真实验验证了所提方法的成像性能和高运算效率。 Simulation results verify the effectiveness of the proposed method the imaging performance and high computing efficiency.