ID 原文 译文
48626 针对现有多目标滤波性能评估方法中存在的目标源分配不合理问题,提出一种新的目标源最优分配方法。 Multi-objective filtering performance in view of the existing evaluation methods existing in the target source distribution is not reasonable, put forward a new source of target optimal allocation method.
48627 所提方法首先利用估计目标的协方差矩阵和标准椭球波门初步检测出虚假估计和漏检目标,然后利用最优分配法完成剩余估计目标和剩余源目标间的分配。 Proposed method firstly estimate of the covariance matrix and the standard ellipsoid wave door preliminary detection of false estimates and residual target, then the optimal allocation method is used to estimate the remaining distribution between the target and the rest of the source.
48628 由于采用马氏距离测度和标准椭球波门,使得目标源分配不受量纲选取的影响且与具体应用背景无关。 Since using markov distance measure and standard ellipsoid wave gate, makes the target source distribution is not affected by dimension selection and has nothing to do with the specific application background.
48629 在此基础上,推广了一种多目标误差距离测度对多目标滤波性能进行评估。 On this basis, to promote a kind of multi-objective error distance measure to evaluate multi-object filtering performance.
48630 实验分析和比较验证了所提方法的合理有效性。 The proposed method is verified by experiment analysis and comparison of reasonable effectiveness.
48631 高技术武器装备技术准备在装备保障中处于非常重要的地位。 High technology weapons and equipment preparation in a very important position in the equipment support.
48632 分析了技术准备的主要环节和要素,给出了效能预测指标体系,建立了基于支持向量机的装备技术准备能力预测算法模型,给出了装备技术准备的保障效能预测实例。 Analyzes the main steps of technical preparation and elements of the index system of performance forecast is given, based on support vector machine equipment technical preparation capacity prediction algorithm model of equipment technology to guarantee effectiveness forecast instance is given.
48633 预测结果证明,所提算法是一种有效的非线性处理方法,建立在统计学习理论基础上,具有明显的泛化特性。 Prediction results show that the proposed algorithm is an effective nonlinear processing method, based on statistical learning theory, has obvious generalization properties.
48634 所提算法为装备保障指挥决策和系统优化设计提供理论依据、技术支持和有效工具。 Proposed algorithm for equipment support command decisions and provide theoretical basis for system optimization design, technical support and effective tools.
48635 针对目前关于目标径向加速度估计的算法存在着采样频率过大及短时条件下精度不高的问题,提出了一种基于压缩感知(compressive sensing,CS)的机动目标径向加速度估计方法。 About target radial acceleration estimation algorithm at the present time the sampling frequency is too large and the problem of short time under the condition of the high accuracy is put forward based on the compression perception (compressive sensing, CS) maneuvering target radial acceleration estimation method.