美军作战概念开发特点及启示

创新军事思想、开发作战概念是推进军事转型和部队建设的关键抓手。美军秉承“创新提炼—集智研讨—实验验证”的作战概念开发机制,采取聚焦联合作战概念开发,以作战能力需求为牵引,通过突破前沿技术和研发关键装备,以法规制度和标准规范为强制约束的做法对于军队转型建设具有重要启示。本文提出,应着眼于军队的使命任务,强化军队作战概念设计,创新作战概念研究方式,形成“聚焦使命任务—研讨演示概念—体系设计概念—检验优化概念—形成概念产品—指导建设实践”的作战概念开发途径,支撑作战概念创新和前瞻性探索研究,并加强体制机制和标准规范建设,通过对作战概念开发的整体设计和约束规范,提升前瞻作战概念对作战实践的创新引领作用,加速推进军队转型建设。     

Moving horizon based wavelet de-noising method of dual-observed geomagnetic signal for nonlinear high spin projectile roll positioning

Phase-frequency characteristics of approximate sinusoidal geomagnetic signals can be used for projectile roll positioning and other high-precision trajectory correction applications. The sinusoidal geomagnetic signal deforms in the exposed and magnetically contaminated environment. In order to preciously recognize the roll information and effectively separate the noise component from the original geomagnetic sequence, based on the error source analysis, we propose a moving horizon based wavelet de-noising method for the dual-observed geomagnetic signal filtering where the captured rough roll frequency value provides reasonable wavelet decomposition and reconstruction level selection basis for sampled sequence; a moving horizon window guarantees real-time performance and non-cumulative calculation amount. The complete geomagnetic data in full ballistic range and three intercepted paragraphs are used for performance assessment. The positioning performance of the moving horizon wavelet de-noising method is compared with the band-pass filter. The results show that both noise reduction techniques improve the positioning accuracy while the wavelet de-noising method is always better than the band-pass filter. These results suggest that the proposed moving horizon based wavelet de-noising method of the dual-observed geomagnetic signal is more applicable for various launch conditions with better positioning performance.     

遥感数据用户需求融合处理技术

遥感数据是国家的基础性和战略性资源,在经济建设、国防建设、抢险救灾、生态环境保护等方面得到了广泛的应用,发挥着越来越重要的作用,各行各业对遥感数据的需求也越来越多。因此,如何提高对地观测资源的利用率,提高服务响应速度成为迫切需要解决的问题。采用自然语言处理技术,提出了一种用户需求融合处理方法,该方法可以有效地融合归并相同或者相似的用户需求,实现一图多用,引入需求预测和需求融合技术以提高需求融合效率,从而提高对地观测资源的利用率,达到事半功倍的效果。     

基于改进协方差控制的传感器管理算法

针对传统的基于协方差控制的传感器管理算法使用全遍历方法所造成的计算量大,以及传感器切换频繁的问题,提出了一种基于改进协方差控制的传感器管理算法。该算法在每一时刻首先判断前一时刻所用传感器组是否能够满足目标跟踪需求,以滤波协方差与期望协方差的偏差作为参考,结合量纲变换和特征值求取,为协方差偏差矩阵经过量纲变换后得到的量纲一致阵的所有特征值设定一个精度阈值,然后判断滤波协方差是否满足期望,从而决定是否维持当前选择的传感器组。在目标作匀速、匀加速、协同转弯等多种场景下进行了算法性能测试分析,仿真结果表明,该算法不仅在大部分场景下满足目标跟踪精度,而且能够提高传感器管理算法的实时性,同时降低传感器的切换频率。     

基于小波包和支持向量机的舰用发动机故障诊断

舰用发动机是一个复杂的大系统,由于受到海洋恶劣气候的影响,其故障发生的概率大大增加,因此,对舰用发动机故障诊断进行研究具有重大实际意义。以舰用发动机的主泵轴承为例,提出了基于小波包和支持向量机的故障诊断方法。首先采用振动加速度传感器获取轴承的振动信号,然后对采集数据进行多层小波包分解,求各频带信号能量,形成各种故障模式下的特征向量。将形成的故障特征向量训练集输入到支持向量机,通过训练建立诊断分类器,并运用测试数据对建立的诊断分类器进行测试。实验结果表明,该方法可以很好地实现舰用发动机故障诊断效能,具有很好的工程应用前景。     

New sources of military change – armed forces as normal organizations

The literature on how European states have adapted to the post-cold war security environment ffocuses invariably on different understandings of military transformation, a process which is seen as inherently different from other forms of organizational change. However, as this paper argues, new management practices, going back to the introduction of so-called New Public Management (NPM) reforms throughout Europe in the 1980s, have eventually penetrated also the last bastion of the old state – the defense sector. Taking a critical approach to the idea of military transformation and existing theories of military change, the paper demonstrates how other international developments have pushed towards what may be seen as a “normalization” of Europe’s defense sectors. This has important implications for how we approach and understand change in contemporary defense organizations.     

军队科研机构推进国防知识产权转化运用

军队科研机构作为国家科技创新体系的重要组成部分,承担了大量科技创新任务,产生了许多具有自主知识产权的高水平科技成果,推动军队科研机构国防知识产权转化运用,是贯彻军民融合发展战略的必要途径。分析了军队科研机构国防知识产权转化的现状及制约转化的现实障碍,并结合实际探讨了推进军队科研机构国防知识产权转化的建议举措。     

Quantitative monitoring of military transformation in the period 1992–2010: Do the protagonists of transformation really change more than other countries?

Military transformation is a complex, slow, asymmetric, changeable, political, and not necessarily completely rational process that clearly needs an effective monitoring mechanism. This paper fills a gap in current literature by creating and testing a model for multi-dimensional and multi-level quantitative monitoring of military transformation applicable in any country. The model is based on 10 transformation indicators that reflect changes in organizational structure, personnel structure, weapon systems, and defense spending. Its application on a sample of seven countries (USA, United Kingdom, France, Netherlands, Poland, Russia, and China) in the period from 1992 to 2010 unexpectedly shows that the USA – a protagonist in the transformation process among allies as well as globally – has carried out the smallest relative change. The non-directed transformation index indicates that Russia carried out 51.8% more change (or 34.1 index units), and the directed index indicates that Poland carried out 157.2% (or 40.8 index units) more change than the USA.     

基于不同能量值特征优选的水声目标识别

采用Bartlet平均周期图、小波变换和经验模态分解方法分别提取信号的频段能量值特征、IMF能量值特征,重点对IMF能量值特征进行特征优选。通过设计BP神经网络分类器,对实测的四类舰船目标的辐射噪声信号进行测试,取得了较好的识别效果。     

基于循环谱相关的雷达信号脉内分析改进算法

针对传统的雷达信号脉内特征分析算法存在的局限,提出了一种基于循环谱相关的雷达信号脉内特征分析的改进算法。该算法将传统的循环谱估计方法进行了改进,能对雷达信号脉内调制方式进行识别并提取脉内特征参数,然后结合改进的小波变换的优点,对识别出的相位编码信号进行相位突变点的提取,最后输出至完善的脉冲描述字中。改进的算法能够在较低计算量的同时保证较好的脉内特征参数的估算精度。仿真结果表明,在较低信噪比下,该算法仍然具有较好的性能。