通过变维kalman滤波实现融合定位

为了能更好地跟踪、定位机动目标,提出了一种将蜂窝网定位信息与本地传感器信息相融合,利用变维Kalman滤波实现定位的方法。本地传感器信息指目标的运动速度和方向。仿真实验证明该方法具有较强的机动跟踪能力,定位精度高,且计算相对简便。     

Mitigation effects on the reflected overpressure of blast shock with water surrounding an explosive in a confined space

The mitigation of blast shock with water has broad application prospects. Understanding the mitigation effects on the reflected overpressure of the explosion shock with water surrounding an explosive in a confined space is of great significance for military explosives safety applications. To estimate the effects of the parameters on the reflected overpressure of blasted shock wave, a series of experiments were carried out in confined containers with spherical explosives immersed in a certain thickness of water, and numerical simulations were conducted to explore the corresponding mechanisms. The results reveal that the reflected overpressure is abnormally aggravated at a small scaled distance. This aggravation is due to the high impulse of the bulk accelerated water shell converted from the explosion. With increasing scaled distance, the energy will be gradually dissipated. The mitigation effects will appear with the dispersed water phase front impacting at a larger scaled distance, except in the case of a dense water phase state. A critical scaled distance range of 0.7—0.8 m/kg1/3 for effective mitigation was found. It is suggested that the scaled distance of space walls should be larger than the critical value for a certain water-to-explosive weight ratio range (5—20).     

水下航行器头部流噪声数值仿真与实验

选取头部线型,对航行器头部基于RNG k-ε湍流模型及FW-H声学模型进行流噪声模拟,然后对3种头部线型的航行器在不同速度下分别进行水洞实验。通过对比分析数值仿真与实验结果发现,航行器头部流噪声随着频率的增大而逐渐减小,随着速度的增大而增大。在相同速度下,与头部线型2、头部线型3相比,头部线型1流噪声较小,具有更好的降噪作用。所采用的计算方法可以比较准确地模拟航行器头部流噪声情况。     

动态威胁环境下单无人机测向定位航迹优化算法

为解决单架无人机在动态战场环境下的测向定位问题,提出了一种基于动态窗口法的单机测向定位航迹优化算法。以最大化Fisher信息矩阵行列式为测向定位评价准则,在由动态探测雷达和静/动障碍构成的动态战场环境中,基于动态窗口法思想,将测向定位航迹优化评价准则由传统的单步最优原则扩展到对多步预测航迹的评价,同时考虑雷达探测和静/动障碍环境对预测航迹的影响,通过滚动时域方法控制无人机最优航向。仿真结果表明,所提方法能够使无人机在有效逃避雷达探测威胁以及规避环境中静/动障碍的条件下保证对目标的高精度测向定位,为解决动态战场环境下的单架无人机测向定位问题提供了新思路。     

基于Dubins路径的智能车辆路径规划算法

路径规划是车辆智能化的核心问题之一,而所有路径均可分解为简单的Dubins路径。在Dubins路径的思想下对智能车辆的行驶路径进行分段研究,并利用经典PID控制对该算法的执行性能进行检验。研究表明:算法能计算出车辆行驶的最短路径,减少了车辆行驶的路径长度,缩短了行驶时间,减少了控制系统的计算量,提高了车辆执行系统的执行力度,降低了执行误差,对最优路径具有较好的选择性。     

Dual-steering mode based on direct yaw moment control for multi-wheel hub motor driven vehicles:Theoretical design and experimental assessment

One of the main challenges for multi-wheel hub motor driven vehicles is the coordination of individual drivetrains to improve mobility and stability in the steering process.This paper proposes a dual-steering mode based on direct yaw moment control for enhancing vehicle steering ability in complex environ-ments.The control system is designed as a hierarchical structure,with a yaw moment decision layer and a driving force distribution layer.In the higher-level layer,the objective optimization function is con-structed to obtain the slip steering ratio,which represents the degree of vehicle slip steering in the dual-steering mode.A yaw moment controller using active disturbance rejection control theory is designed for continuous yaw rate control.When the actual yaw rate of the vehicle deviates from the reference yaw rate obtained by the vehicle reference model and the slip steering ratio,the yaw moment controller is actuated to determine the yaw moment demand for vehicle steering.In the lower-level layer,there is a torque distribution controller based on distribution rules,which meets the requirement of yaw moment demand without affecting the total longitudinal driving force of the vehicle.For verifying the validity and feasibility of the dual-steering mode,simulations were conducted on the hardware-in-loop real-time simulation platform.Additionally,corresponding real vehicle tests were carried out on an eight-wheel prototype vehicle.Test results were generally consistent with the simulation results,thereby demon-strating that the proposed dual-steering mode reduces steering radius and enhances the steering per-formance of the vehicle.     

A melt-cast Duan-Zhang-Kim mesoscopic reaction rate model and experiment for shock initiation of melt-cast explosives

A melt-cast Duan-Zhang-Kim (DZK) mesoscopic reaction rate model is developed for the shock initiation of melt-cast explosives based on the pore collapse hot-spot ignition mechanism. A series of shock initiation experiments was performed for the Comp B melt-cast explosive to estimate effects of the loading pressure and the particle size of granular explosive component, and the mesoscopic model is validated against the experimental data. Further numerical simulations indicate that the initial density and formula proportion greatly affect the hot-spot ignition of melt-cast explosives.     

自主水下航行器的自适应反演变结构控制器设计

由于水下航行器是高度耦合、复杂的多输入多输出不确定性非线性系统。对水下航行器进行精确作业时的运动控制一直是其实用化过程中困扰人们的问题。将自适应反演控制技术和变结构控制策略相结合,提出了一种基于反演技术的自适应变结构控制器设计方法,实现AUV水平侧移和航向控制,并利用自主水下航行器模型进行了仿真研究。仿真结果表明,该控制方法对模型不确定性和不确定环境干扰表现出良好的鲁棒性和自适应性。     

一类三维混沌系统的T—S模糊控制

针对一类三维混沌系统,在用T—S模糊模型重构该系统的基础上,利用反馈控制思想和并行分布补偿（PDC）技术,基于Lyapunov理论为该系统设计了状态反馈控制器．利用线性矩阵不等式（LMI）可求出模糊控制器的参数,实现以衰减率a全局渐近稳定．对该系统的一个重要特例—ADVP系统的仿真结果验证了该控制方法的有效性．     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

水下缩比航行体热尾流的红外探测实验研究

根据缩比模型,建立了缩比红外成像实验测试系统,对水下航行体的体积、航行深度、运动速度、尾流排放等进行了缩比设计,设计了多种实验工况,可实现缩比目标模型红外尾流的静态和动态测试,一方面明确红外尾流的可探测性,另一方面掌握红外尾流可探测性的影响因素以及红外尾流的变化规律,为下一步工作奠定基础。     

基于MATD的高超声速飞行器反演控制

针对高超声速飞行器弹性体模型,提出了一种基于改进的反正切跟踪微分器(MATD)的鲁棒反演控制器。将控制系统分为高度和速度子系统,采用反演方法设计虚拟控制量和实际控制量。引入MATD对高阶系统虚拟控制量求导,避免了传统反演方法"微分膨胀"的问题。基于MATD设计干扰观测器,对模型不确定项进行精确估计,增强了控制器的鲁棒性。最后,通过实例仿真验证,该控制器对速度和高度指令具有很好的跟踪效果,且具有较强的鲁棒性。     

The many-product cargo loading problem

An algorithm, based upon dynamic programming, is developed for a class of fixed-cost cargo loading problems. The problems can be formulated as integer programming problems, but cannot be efficiently solved as such because of computational difficulties. The algorithm developed has proved to be very efficient in an actual operations research study involving over 500 different cargo items, more than 40 possible stops and several types of transportation vehicles. A numerical illustration is provided.     

国外潜航器水下隐蔽导航定位方法探析

针对潜航器自主惯性导航误差随时间不断增大的问题，研究了基于运载器、信标中继、海底固定基站的国外潜航器的典型导航定位方法。通过水声通信方式，运载器、信标中继站将其卫星精确定位数据发送至潜航器，或海底固定基站接收到潜航器发射唤醒信号后，量测相关信息并发至潜航器。潜航器被动接收水声通信数据，并对其进行综合处理，实现潜航器在水下隐蔽工作模式下对自身位置的实时修正，提高潜航器导航定位精度，具备较强的工程可实现性。     

车载多接入边缘网络中联合资源分配和动态任务卸载方案

针对车联网中车辆移动速度过快产生的任务卸载失败问题,设计了一个有效的任务卸载风险评估模型,并提出了联合资源分配的动态任务卸载方案。将时间、能耗和风险共同建模为系统效用,通过联合优化卸载决策、资源分配来最大化系统效用。优化问题被公式化为混合整数非线性规划,在给定卸载决策的情况下,利用凸优化技术解决计算资源分配问题,功率分配通过分式规划技术来优化。仿真分析了车辆移动性对系统效用的影响,证明了所提方案的合理性。     

军用电传动车辆混合动力系统能量管理技术

混合动力系统是军用电传动车辆具有优越性能的基础,能量管理技术则负责实现负载需求在系统中各动力源间的合理分流及部件的优化控制,是军用车辆混合动力系统研究的关键技术之一。分析了军用车辆混合动力系统的特点,研究了其对系统能量管理的影响,总结了当前能量管理技术研究现状,最终,针对当前能量管理技术存在的问题提出了相应的解决方案。     

高超声速滑翔式飞行器再入轨迹多目标多约束优化

轨迹优化是高超声速滑翔式飞行器关键技术之一.为避免间接法求解轨迹优化问题时对初值敏感以及伪谱法求解轨迹优化问题中难以处理航路点和禁飞区等问题,提出采用基于Akima插值多项式的直接法求解高超声速滑翔式飞行器再入轨迹优化问题.以驻点热流密度最小和到达目标点时间最小为优化目标,考虑了终端约束、航路点约束、禁飞区约束、动压约束、过载约束等约束条件.仿真结果表明:采用的插值方法可以减少插值过程中的控制变量越界问题;得到的Pareto前沿具有良好的分布性,在初步设计时能够给设计者较大的选择余地;和文献中的单目标优化结果相比,本文所采用的算法也具有较好的寻优能力.     

无人车用智能导航技术国际态势分析

根据无人车用智能导航技术相关的研究与综述论文、专利发表情况,对该专业技术领域进行总体分析。选取1990—2020年的数据,针对论文发表情况,主要对其发展趋势、国家/地区分布、机构分布、出版物分布、高被引论文、被引频次和研究主题进行深入分析;针对专利申请现状,主要对专利申请时间、国家/地区分布、专利权人、专利研发技术热点等进行深入分析。研究结果表明,在无人车用智能导航技术研究领域,美国和中国无论在论文还是专利的数量和质量方面,均处于世界前列。该技术领域的研究热点主要集中在导航系统、导航卫星、惯性技术、地球物理数据、自主车辆导航、自主车辆定位、激光雷达、位置数据、神经网络、目标跟踪算法、传感器、卷积神经网络、自动驾驶等方面。     

高速履带车辆在坚实地面转向机理研究

运用系统分析的方法,研究坚实地面条件下高速履带车辆转向过程理论及其计算机仿真。以履带滑动转向理论为基础,考虑影响履带车辆转向的诸多因素(质心位置、负荷分布等),建立了履带车辆转向过程动力学模型。并为求解模型中的微分一代数混合方程,编写相应程序进行了仿真计算,对高低速2种情况下高速履带车辆的转向过程进行了计算机仿真实验,仿真计算的结果与实车野外实验的结果呈现一致性。特别在分析履带车辆高速转向过程中研究了离心力通过履带接地压力而对履带车辆转向过程的影响。     

多无人机协作侦察中的车辆再识别

在多无人机协作侦察中,匹配识别不同无人机侦察发现的装甲车辆,属于车辆再识别任务。近年来,车辆再识别技术在智能交通领域得到了快速发展,但是该技术尚未在军事领域得到充分的关注和应用。本文围绕该技术的发展和军事应用展开研究,一方面,从数据集、特征表示、注意力学习、度量学习、属性学习等方面对民用车辆再识别技术进展进行综述,分析总结了现有技术的优点和劣势,提出了有待深入探索的研究方向;另一方面,以多无人机协作侦察任务为背景,探讨分析了车辆再识别在其中的作战运用方式,并针对战场上存在的计算资源有限、环境复杂多变等因素导致车辆再识别性能下降问题,提出了可能的解决思路。本文研究可为车辆再识别技术在多无人机协作侦察中的应用提供前瞻性参考。