Investigation on the spatial distribution characteristics of behind-armor debris formed by the perforation of EFP through steel target

The behind-armor debris (BAD) formed by the perforation of an EFP is the main damage factor for the secondary destruction to the behind-armor components. Aiming at investigating the BAD caused by EFP, flash X-ray radiography combined with an experimental witness plate test method was used, and the FEM-SPH adaptive conversion algorithm in LS-DYNA software was employed to model the perforation process. The simulation results of the debris cloud shape and number of debris were in good agreement with the flash X-ray radiographs and perforated holes on the witness plate, respectively. Three-dimensional numerical simulations of EFP's penetration under various impact conditions were conducted. The results show that, an ellipsoidal debris cloud, with the major-to-minor axis radio (a/b) smaller than that caused by shaped charge jets, was formed behind the target. With the increase of target thickness (h) and decrease of impact velocity (v₀) and obliquity (θ), the value of a/b decreases. The number of debris ejected from target is significantly higher than that from EFP. Based on the statistical analysis of the spatial distribution of the BAD, An engineering calculation model was established considering the influence of h, v₀ and θ. The model can with reasonable accuracy predict the quantity and velocity distribution characteristics of BAD formed by EFP.     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

考虑禁飞区的高超声速飞行器再入跟踪控制

为确立高超声速飞行器再入精确模型,参考NASA的研究数据对动力学方程中的气动参数进行拟合。基于飞行器结构的相关性质及战略应用背景,加入热流密度、动压、过载和禁飞区等参考约束的限制,融合成强非线性、复杂耦合的最优控制问题。采用改进自适应伪谱法求解模型所构建的微分方程组,通过设置自适应网格细化与配点,使单位时间内状态变量和控制变量波动过大的时间区间被进一步细划,并利用SNOPT求解器解算出符合条件的最优轨迹。设计闭环控制器,实现对最优轨迹的姿态变化的跟踪,测试系统的性能并进行评估。仿真结果表明:整个再入过程中,飞行器速度下降过程偏于平稳,再入轨迹可以满足约束条件,在避开禁飞区的同时取得最大横向航程;三通道角速度收敛可控,对姿态的跟踪较理想,控制器基本可以实现精确调姿。     

共址调频和调幅系统干扰机理及干扰抑制需求分析

以调幅和调频电台为研究对象,对共平台接收电台前端低噪声放大器的非线性进行精确建模,分别对调幅电台和调频电台的干扰抑制需求进行解析,并通过数值仿真对解析模型进行验证。结果表明:所提解析模型较现有模型更为准确;当有用信号功率、噪声功率和干扰功率相同时,调幅通信系统的干扰抑制需求高于调频通信系统。     

基于正态分布曲线的分段式变步长LMS算法

针对传统最小均方误差(Least Mean Square, LMS)自适应滤波算法由于步长固定,在解决稳态误差与收敛性之间的关系时,始终处于矛盾状态的问题,在对传统的固定步长LMS自适应滤波算法分析的基础上,根据变步长LMS自适应滤波算法的步长调整原则,通过构造步长因子与误差信号的非线性函数,提出了一种基于正态分布曲线的分段式变步长LMS自适应滤波算法,并分析了参数取值对算法性能的影响。针对实际信号处理过程中参考信号难以选取的问题,提出了一种基于分裂阵的参考信号选取方法。理论和海试数据分析结果表明:该算法的收敛速度和稳态误差明显优于固定步长的LMS自适应滤波算法和基于Sigmoid函数的变步长LMS自适应滤波算法。     

自适应采样数粒子滤波算法

基于统计决策规则提出自适应采样数粒子滤波算法,在定义综合性能风险函数的基础上,推导出粒子数与滤波误差方差之间的关系式,使得在跟踪过程中,可以根据目标的机动情况在线调节粒子数,以使跟踪性能达到最优。在Matlab仿真平台下进行了闪烁噪声下的机动目标跟踪实验,结果表明,自适应采样数粒子滤波算法是一种有效的机动目标跟踪方法,跟踪性能较基本粒子滤波算法提高了3.7倍。     

儒家生态伦理思想及其当代价值探析

儒家的生态伦理思想以＂天人合一＂为基础,以＂仁爱万物＂的生态价值观为指导,强调要遵循自然规律,提倡＂取物不尽物＂的生态资源节用观。现时代发掘和弘扬儒家的生态伦理思想,对于我们解决当代社会生态危机,优化生态环境,重建人与自然的和谐具有重大意义。     

基于门限的无线传感器网络密钥管理方案

由于无线传感器网络在能量消耗、内存开销和计算能力等方面的局限性,传统的网络密钥管理方法已不适用。为此提出了一种适用于无线传感器网络的密钥预分配方法——基于（t,n）-门限方案,给出了密钥分配方法,并从方案的连通性、安全性等方面进行了有效的分析,结果表明该算法在这些方面有一定的优势。     

强背景噪声下电晕放电辐射信号小波阈值去噪和分析

分析电晕放电信号小波阈值去噪中小波基函数的最优选取、分解层数及阈值的确定,并对实测电晕放电信号进行小波阈值去噪。结果表明,选取db8小波作为最优小波基函数,选取双变量阈值函数作为小波阈值函数对电晕放电信号进行小波阈值去噪,放电辐射信号与背景噪声可以得到有效分离,具有很好的去噪效果。     

GM（1，1）组合优化模型

从影响GM（1,1）模型产生误差的两个主要原因出发,重新选择灰导数,并基于Newton．Cote’s积分公式和相邻最近插值方法构造出GM（1,1）组合模型,提出了求该组合模型参数的计算方法,通过实例验证了组合模型的模拟精度,具有重要的应用价值。