海战场预警探测感知度建模与计算

为量化海战场预警探测系统的信息获取能力,引入感知度概念,建立了战场感知度数学模型,给出了感知度的计算流程、方法及步骤,并对不同观察区域的感知度计算进行分析。通过建模与计算,可对现有预警探测系统信息获取能力进行评估,具有较好的海战场应用价值。     

飞行器MDO中灵敏度计算的自动微分方法

自动微分方法(ADM)是灵敏度计算的一种新方法,是处理飞行器多学科设计优化中灵敏度分析问题的有力工具。将ADM与估算灵敏度最常用的有限差分方法(FDM)以及与ADM同时期发展起来的另外一种灵敏度计算方法—复变量方法(CVM),从原理上进行了比较,研究了ADM前向模式在Visual C 6.0环境中的实现方法,结合多学科环境中的飞行器设计优化计算实例分析了该模式的优缺点。ADM在科学计算、工程计算等方面有很大的发展空间。     

Effects of cueing in cooperative search

We consider the effects of cueing in a cooperative search mission that involves several autonomous agents. Two scenarios are discussed: one in which the search is conducted by a number of identical search‐and‐engage vehicles and one where these vehicles are assisted by a search‐only (reconnaissance) asset. The cooperation between the autonomous agents is facilitated via cueing, i.e., the information transmitted to the agents by a searcher that has just detected a target. The effect of cueing on the target detection probability is derived from first principles using a Markov chain analysis. In particular, it is demonstrated that the benefit of cueing on the system's effectiveness is bounded. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Electronic warfare in the optical band: Main features,examples and selected measurement data

The paper presents the possibilities of, and methods for, acquiring, analysing and processing optical signals in order to recognise, identify and counteract threats on the contemporary battleground. The main ways electronic warfare is waged in the optical band of the electromagnetic wave spectrum have been formulated, including the acquisition of optical emitter signatures, as well as ultraviolet (UV) and thermal (IR) signatures. The physical parameters and values describing the emission of laser radiation are discussed, including their importance in terms of creating optical signatures. Moreover, it has been shown that in the transformation of optical signals into signatures, only their spectral and temporal parameters can be applied. This was confirmed in experimental part of the paper, which includes our own measurements of spectral and temporal emission characteristics for three types of binocular laser rangefinders. It has been further shown that through simple registration and quick analysis involving comparison of emission time parameters in the case of UV signatures in “solar-blind” band, various events can be identified quickly and faultlessly. The same is true for IR signatures, where the amplitudes of the recorded signal for several wavelengths are compared. This was confirmed experimentally for UV signatures by registering and then analyzing signals from several events during military exercises at a training ground, namely Rocket Propelled Grenade (RPG) launches and explosions after hitting targets, trinitrotoluene (TNT) explosions, firing armour-piercing, fin-stabilised, discarding sabots (APFSDS) or high explosive (HE) projectiles. The final section describes a proposed model database of emitters, created as a result of analysing and transforming the recorded signals into optical signatures.     

An experiment evaluating how the tiny mass eccentricities in spin-stabilized projectiles affect the position of impact points

This study investigates and quantifies some possible sources affecting the position of impact points of small caliber spin-stabilized projectiles (such as 12.7 mm bullets). A comparative experiment utilizing the control variable method was designed to figure out the influence of tiny eccentric centroids on the projectiles. The study critically analyzes data obtained from characteristic parameter measurements and precision trials. It also combines Sobol's algorithm with an artificial intelligence algorithm—Adaptive Neuro-Fuzzy Inference Systems (ANFIS)—in order to conduct global sensitivity analysis and determine which parameters were most influential. The results indicate that the impact points of projectiles with an entry angle of 0° deflected to the left to that of projectiles with an entry angle of 90°. The difference of the mean coordinates of impact points was about 12.61 cm at a target range of 200 m. Variance analysis indicated that the entry angle — i.e. the initial position of mass eccentricity — had a notable influence. After global sensitivity analysis, the significance of the effect of mass eccentricity was confirmed again and the most influential factors were determined to be the axial moment and transverse moment of inertia (Izz Iyy), the mass of a projectile (m), the distance between nose and center of mass along the symmetry axis for a projectile (Lm), and the eccentric distance of the centroid (Lr). The results imply that the control scheme by means of modifying mass center (moving mass or mass eccentricity) is promising for designing small-caliber spin-stabilized projectiles.     

Bidirectional parallel multi-branch convolution feature pyramid network for target detection in aerial images of swarm UAVs

In this paper, based on a bidirectional parallel multi-branch feature pyramid network (BPMFPN), a novel one-stage object detector called BPMFPN Det is proposed for real-time detection of ground multi-scale targets by swarm unmanned aerial vehicles (UAVs). First, the bidirectional parallel multi-branch convolution modules are used to construct the feature pyramid to enhance the feature expression abilities of different scale feature layers. Next, the feature pyramid is integrated into the single-stage object detection framework to ensure real-time performance. In order to validate the effectiveness of the proposed algorithm, experiments are conducted on four datasets. For the PASCAL VOC dataset, the proposed algorithm achieves the mean average precision (mAP) of 85.4 on the VOC 2007 test set. With regard to the detection in optical remote sensing (DIOR) dataset, the proposed algorithm achieves 73.9 mAP. For vehicle detection in aerial imagery (VEDAI) dataset, the detection accuracy of small land vehicle (slv) targets reaches 97.4 mAP. For unmanned aerial vehicle detection and tracking (UAVDT) dataset, the proposed BPMFPN Det achieves the mAP of 48.75. Compared with the previous state-of-the-art methods, the results obtained by the proposed algorithm are more competitive. The experimental results demonstrate that the proposed algorithm can effectively solve the problem of real-time detection of ground multi-scale targets in aerial images of swarm UAVs.     

Preparation and characterization of HMX/EVA/hBNNSs micro-composites with improved thermal stability and reduced sensitivity

Hexagonal boron nitride nanosheets(HBNNSs)have huge potential in the field of coating materials owing to their remarkable chemical stability,mechanical strength and thermal conductivity.Thin-layer hBNNSs were obtained by a liquid-phase exfoliation of h-BN powders and incorporated into EVA coatings for improving the safety performance of 1,3,5,7-tetranitro-1,3,5,7-tetrazocane(HMX).HBNNSs and ethylene-vinyl acetate copolymer(EVA)were introduced to HMX by a solvent-slurry process.For com-parison,the HMX/EVA and HMX/EVA/graphene(HMX/EVA/G)composites were also prepared by a similar process.The morphology,crystal form,surface element distribution,thermal decomposition property and impact sensitivity of HMX/EVA/hBNNSs composites were contrastively investigated.Results showed that as prepared HMX/EVA/hBNNSs composites were well coated with hBNNSs and EVA,and exhibited better thermal stability and lower impact sensitivity than that of HMX/EVA and HMX/EVA/G composites,suggesting superior performance of desensitization of hBNNSs in explosives.     

自然场景车标数据集的构建及其应用

车标作为车辆身份的关键特征之一,在车辆的监控与辨识中发挥着重要作用。由于自然场景复杂多变,对其中的车标进行准确识别仍具有很大的挑战性。目前公开数据库很少且存在诸多局限,导致研究缺乏可信度和实用性。本文建立了一个面向自然场景的全新数据集,包含多种采集环境下的10 324幅、67类车辆图像。基于此数据集开展应用研究,提出一个目标检测与深度学习相结合的车标识别方法,包括车标区域定位和车标种类预测两大步骤。实验表明,该方法对复杂背景有较强的适应性,在涉及30种车标的分类任务中达到89.0%的总体识别率。     

潜艇自航模水下长波遥控系统

提出了利用无线长波对水下潜艇自航模进行长波遥控的通信技术,阐述了长波遥控的发射、接收及天线系统的硬件组成和系统设计。对发射天线的现场测试结果进行了分析,提出了实际电路的阻抗匹配实现方法;对接收信号的噪声和灵敏度等有关问题进行了分析,采用天线的方向性自适应控制技术解决了潜艇水下接收,在实际应用中取得较好的效果。     

一种基于生物免疫原理的入侵检测新模型

入侵检测系统可以从生物免疫系统的很多特点中得到启发,文中利用生物免疫原理设计了一个新的入侵检测框架模型,该框架在传统信息传输网基础上构建了免疫淋巴网,用来监控和管理传统传输网的行为。模型中还应用了阴性选择、克隆选择等免疫算法,使得该模型对于入侵检测问题有较好的敌我识别功能。