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.     

坦克嵌入式训练系统信息采集与处理技术

以坦克嵌入式训练为对象,分析了训练中信息采集与处理任务的功能及特点,并结合某新型坦克的技术特点,提出了信息采集与处理任务的需求,建立了分布式附加结构的信息采集处理模型。模型采用模块化和总线互联结构,由功能独立的主控单元和采集单元构成,保证了实车信息采集与处理的实时性和可靠性。     

一种传感器网格自协同作战模型*

传统的协同技术不能满足传感器网格复杂的协同应用在动态性、实时性以及分布决策的强协同等方面的需求。为此,建立了一种自协同技术,给出了自协同作战虚拟组织(ACBVO)的参量化描述,提出了传感器网格自协同作战模型(SGACBM),描述了协同成员的信息结构和功能结构。使用SGACBM,ACBVO能在执行任务过程中,不断监测协同工作的质量,并根据协同质量动态切换协同机制。SGACBM能改善传感器网格的协同质量,加速作战进程,实现传感器网格自协同作战。     

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。     

三关节机器人的神经网络补偿自适应控制器设计

三关节机器人广泛用于工业生产、轮式或履带式排爆机器人,为了补偿由于机器人结构参数、作业环境干扰等不确定性因素造成的机器人动力学模型的不确定性,将机器人动力学模型分解为名义模型和误差模型两部分,其误差模型采用RBF神经网络进行补偿,得到其估计信息,神经网络的输出权值根据Lyapunov稳定性理论采用自适应算法进行调整。所设计的神经网络补偿自适应控制器解决了不确定性机器人动力学系统控制器设计的不确定性问题,同时,通过定义Lyapunov函数,证明了控制器能渐近、稳定地跟踪期望轨迹。机器人的3个关节在控制器的作用下,约在5 s时达到期望轨迹,神经网络约在5 s时逼近机器人动力学模型的误差模型,实验结果表明了机器人关节对期望轨迹具有良好的轨迹跟踪性能。     

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.     

美“海军一体化火力控制--制空”能力发展现状与启示

美“海军一体化火力控制－制空”（ NIFC－CA）是美军海上盾牌防御体系概念的重要组成部分。该体系经过多年的发展已初见成效。首先，对美“海军一体化火力控制———制空”的基本概念及内涵进行了阐述，对其主要组成CEC、E－2D预警机、宙斯盾系统及标准－6舰空导弹在防御体系中的功能进行了分析；然后，介绍了美NIFC－CA的6种主要指挥控制模式，并对其协同指挥决策模式进行了分析，得出了指挥决策分布处理的特点；最后，总结了美NIFC－CA发展对我海军海上防御力量发展建设的启示。     

集中式组网雷达假目标干扰建模

针对集中式组网雷达数据处理算法的薄弱环节,通过对集中式组网雷达假目标干扰问题的研究,建立了密集假目标干扰、航迹扰乱干扰和航迹欺骗干扰三类假目标干扰模型。首先介绍了集中式组网雷达的数据处理算法,分析了这种算法对于假目标干扰的薄弱环节,针对薄弱环节提出了上述三种假目标干扰类型。然后给出了这三种类型假目标干扰的概念、产生方法、数学模型和运用方式;最后分析了组网雷达的抗干扰措施对于假目标干扰的影响。     

导弹毁伤机场目标的信息处理技术

立足现实作战需求 ,运用多种图像处理方法和模式识别方法 ,研究目标实际毁伤信息的综合提取和处理方法 ,重点研究机场类目标的毁伤信息处理技术 ,建立了该类典型目标的打击效果判定系统。     

一种提高智能光轴检测系统定位精度的方法

针对目前各种光轴检测装置普遍存在精度不高的问题 ,基于CCD智能光轴检测系统 ,提出了一种细分插值的算法。实验表明 ,该算法的软件实现可以将像点的位置坐标提高到亚微米级。