共查询到17条相似文献,搜索用时 171 毫秒
1.
针对舰艇对空防御空中目标威胁判断指标属性权重与属性值均为区间数的情况,通过以各方案与理想方案偏差最小、与负理想方案偏差最大,以及权系数熵的最大化为优化目标,用拉格朗口乘子法给出模型的最优解,得到指标的权重值;基于区间数的4种不同的距离度量方式,建立基于TOPSIS法的威胁判断模型;通过实例对比在不同距离度量下的排序效果... 相似文献
2.
3.
基于矩阵奇异值理论的颤振分析新方法 总被引:1,自引:0,他引:1
根据颤振分析的基本概念,提出了一类基于矩阵奇异值理论的颤振分析新方法。该方法的特点是,以计算颤振矩阵最小奇异值或条件数的倒数来直接搜索颤振临界点。证明了这两个指标在颤振临界点处的等价性。根据指标在颤振临界点附近取极小值的特点,编制了相应的算法,在确定颤振临界点时无需计算颤振特征根,避免了“窜支”问题,从而减少了人工干预,提高了计算自动化程度。数值算例结果表明,采用该方法计算得到的颤振临界速度和颤振频率与p-k法计算结果的精度相当,且两个指标对应的计算结果一致,验证了其等价性。 相似文献
4.
针对导弹状态评估过程主观性强、结论简单粗放等问题,提出1种基于组合赋权-改进理想解法(TOPSIS)的导弹状态评估方法.首先,深入分析导弹状态影响因素,构建导弹状态评估指标体系;然后,综合运用模糊层次分析法与熵权法计算各指标的组合权重,提出通过导弹状态标准参数来确定TOPSIS模型的正、负理想解,并将正、负理想解的距离... 相似文献
5.
提出了1种基于多目标遗传算法以及多属性决策的PID参数设计方法,综合考虑了系统超调量、稳定时间和ITAE指标,采用改进非支配解排序的多目标遗传算法(NSGAII)求出了Paret0最优解;用这些Pareto最优解构成决策矩阵,使用客观赋权的信息熵法对最优解的属性进行了权值计算,然后采用逼近理想解的排序方法(TOPSIS)进行了多属性决策(MADM)研究,对Pareto最优解给出了排序;计算了某型航空发动机PID控制的数值算例,结果表明所提出的联合方法通用性好,所设计的PID性能优异,适合工程实际应用。 相似文献
6.
基于SVD的R-T-S最优平滑在机载SAR运动补偿POS系统中的应用 总被引:1,自引:0,他引:1
机载合成孔径雷达(SAR)运动补偿用位置姿态系统(POS)的导航精度直接影响SAR成像的效果。为进一步提高POS的导航精度和数值稳定性,提出将基于奇异值分解(SVD)的Rauch-Tung-Striebel(R-T-S)最优固定区间平滑应用于POS后处理中。在基于SVD的前向卡尔曼滤波(KF)的基础上,进行了基于SVD的后向R-T-S最优固定区间平滑,获得位置、速度和姿态的最优估计。该方法将原算法中均方误差阵进行奇异值分解,不仅具有很好的数值稳定性和鲁棒性,而且避免了矩阵的求逆。半物理仿真结果表明,该方法在导航精度和数据平滑度上明显优于目前工程中应用的KF,是一种有效的事后处理方法。 相似文献
7.
基于全球定位系统(GPS)快速定位中观测矩阵的病态性特点和Tikhonov正则化原理,研究了单频整周模糊度快速解算的改进方法.基于奇异值扰动理论,研究了改进型UDVT分解算法,即利用病态观测矩阵构造新的矩阵,然后化为上Hessenberg形式的三对角矩阵,利用移位QR算法得到精确的奇异值,避免了因较小奇异值发生较大抖动而使正则化矩阵出现不稳定的情况;在分析法矩阵病态性特点的基础上,设计了改善正则化矩阵的构造方法.实验结果表明,与传统最小二乘降相关平差(LAMBDA)算法和Tikhonov正则化-LAMBDA法相比,新算法能更有效地改善法矩阵的病态性,只利用3~5个历元即能实现模糊度浮点解的快速解算及其固定,且结果可靠,浮点值更加接近真实值. 相似文献
8.
9.
10.
针对空间相干信源的波达方向估计问题,提出了一种基于协方差矩阵重构的TSVD-ESPRIT算法。它利用包含所有信源信息的特征向量构造Toeplitz协方差矩阵,避免了阵列有效孔径的损失,分辨率高且稳定性好;并且利用ESPRIT算法代替MUSIC算法进行DOA估计,避免了谱峰搜索,大大降低了计算量。数据仿真和分析证明了该算法的正确性和有效性。 相似文献
11.
卫星导航抗干扰的过程中,对空间信号波达方向估计、干扰个数检测、最优权矢量的求解直接影响着导航接收机的抗干扰性能,而协方差矩阵的特征分解是这些算法实现的核心部分。根据自适应阵列天线获得的协方差矩阵的特性,基于双边并行Jacobi算法,实现了基于FPGA的协方差矩阵特征值和特征向量的求解,并通过在信号波达方向估计的应用进行了验证。另外,在实现的过程中对直接调用CORDIC IP核的方式进行了精度误差分析,并用一种双精度浮点的方式进行修正,提高了矩阵特征分解FPGA的实现精度,为导航抗干扰接收机性能的提升提供了有效的工程基础。 相似文献
12.
"Artificial noise," or the connection of feedback paths around the the integrators, is shown to be an effective method of dealing with the problem of multiplier offsets in adaptive antennas. This probl which was analyzed by Compton [1] is particularly troubles when the covariance matrix is singular or nearly so. Like added real noise, the artificial noise improves the condition number of the underlying matrix. The artificial noise, however, avoids the obvious disadvantage of adding to the real noise level. As a result the output-signal-to-interference ratio is much less degraded. 相似文献
13.
14.
The Modified Yule-Walker Method of ARMA Spectral Estimation 总被引:2,自引:0,他引:2
An overview of ARMA spectral estimation techniques based on the modified Yule-Walker equations is presented. The importance of using order overestimation, as well as of using an overdetermined set of equations, is emphasized. The Akaike information criterion is proposed for determining the equation order. A procedure for removing spurious noise modes based on modal decomposition of the sample covariance matrix is derived. The role of the singular value decomposition method in solving the modified Yule-Walker equations is discussed. A number of techniques for estimating MA spectral parameters are presented. 相似文献
15.
16.
针对稀疏分解方法进行均匀圆阵(UCA)的二维波达方向(DOA)估计运算复杂度大的问题,提出了一种基于协方差矩阵高阶幂稀疏分解的二维DOA估计新算法。该算法首先利用协方差矩阵高阶幂无需进行特征值分解和信源数估计的特性,构建了协方差矩阵高阶幂的稀疏分解向量;然后运用粒度分层思想,构造了粗区域估计和细方位估计的分层多粒度的快速分解模型,分层字典的长度大大减少,在保持估计精度的前提下,算法运算时间远小于现有的恒定冗余字典的稀疏分解方法,从而解决了基于稀疏分解的圆阵二维DOA估计问题。论文提出的算法与二维MUSIC算法相比,估计精度高,且能满足对相干信号的估计。仿真结果验证了算法的有效性和可行性。 相似文献
17.
The use of adaptive linear techniques to solve signal processing problems is needed particularly when the interference environment external to the signal processor (such as for a radar or communication system) is not known a priori. Due to this lack of knowledge of an external environment, adaptive techniques require a certain amount of data to cancel the external interference. The number of statistically independent samples per input sensor required so that the performance of the adaptive processor is close (nominally within 3 dB) to the optimum is called the convergence measure of effectiveness (MOE) of the processor. The minimization of the convergence MOE is important since in many environments the external interference changes rapidly with time. Although there are heuristic techniques in the literature that provide fast convergence for particular problems, there is currently not a general solution for arbitrary interference that is derived via classical theory. A maximum likelihood (ML) solution (under the assumption that the input interference is Gaussian) is derived here for a structured covariance matrix that has the form of the identity matrix plus an unknown positive semi-definite Hermitian (PSDH) matrix. This covariance matrix form is often valid in realistic interference scenarios for radar and communication systems. Using this ML estimate, simulation results are given that show that the convergence is much faster than the often-used sample matrix inversion method. In addition, the ML solution for a structured covariance matrix that has the aforementioned form where the scale factor on the identity matrix is arbitrarily lower-bounded, is derived. Finally, an efficient implementation is presented. 相似文献