JTIDS自组织组网路由协议及性能分析

文章在分析JTIDS数据链系统消息的基础上,提出了一种支持地面组网的路由协议(JMR),在不改动现有消息内容的前提下,可以实现JTIDS端机间的无中心自组织组网,并对时延、吞吐量、交付率、路由开销等方面性能进行了仿真分析。     

【专题】面向精打产品的红外图像数据采集、治理和应用

面对复杂严酷的战场环境,红外成像精打产品的智能化水平和抗干扰能力是产品生存的重要因素,而图像大数据技术是红外成像精打产品提升技术能力的重要保障。本文结合红外成像精打产品智能化能力提升的需求,提出了面向精打产品的图像数据获取、历史数据及新增数据治理、数据挖掘应用的全过程实用方法,实现了特定目标红外图像数据增补及海量图像数据的高效管理与智能应用;并在图像大数据的支持下,研发了智能信息处理算法性能评价平台和目标检测算法,有效提升了精打产品的智能化水平和实际应用能力。开展基于实际应用需求的图像数据采集、治理和应用技术研究是提升精打产品性能的重要途径,也能够为智能信息处理技术在精打产品上的落地应用提供有力支撑。     

Numerical modelling of non-ideal detonation in ANFO explosives applying Wood-Kirkwood theory coupled with EXPLO5 thermochemical code

Ammonium nitrate and fuel oil (ANFO) based explosive is a classic example of non-ideal high explosives. Its detonation is characterized by a strong dependence of detonation parameters on explosive charge diameter, presence and characteristics of confinement, as well as incomplete consumption of explosive at the sonic point.In this work we propose a detonation model based on the Wood-Kirkwood (WK) theory coupled with the thermochemical code EXPLO5 and supplemented with reaction rate models. Our objective is to analyze the validity of the model for highly non-ideal ANFO explosives, with emphasis on effect of reaction rate models.It was found that both single-step and two-step pressure-based models can be calibrated to reproduce experimental detonation velocity-charge radius data of ANFO at radii significantly above the failure radius (i.e. for D/D_id > ∼0.6). Single-step pressure-based model, with the pressure exponent equal to 1.4, proved to be the most accurate, even in the vicinity of the failure radius. The impact of the rate models is most evident on temporal (and spatial) distribution of flow parameters in detonation driving zone, especially when it comes to the conversion and width of detonation driving zone.     

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.     

Transverse relaxation characteristic and stress relaxation model considering molecular chains of HTPB coating based on pre-strained thermal aging

In order to accurately describe the transverse relaxation characteristic and stress relaxation modulus of HTPB coating during pre-strain thermal aging process, a one month thermal aging test was carried out at 70 C with pre-strain of 0％, 3％, 6％ and 9％, respectively. The low-field 1H NMR and stress relaxation modulus tests were carried out for HTPB coating at different aging stages. The stress relaxation model considering the molecular chains was proposed according to the changes of crosslinking chain and dangling chain of HTPB coating during pre-strain aging. The results showed that with the increase of aging time, the decay rate of transverse relaxation curve became faster, the transverse relaxation time decreased, the value of combined parameter qMrl increased, the proportion of crosslinking chain decreased, while the proportion of dangling chain increased. Moreover, the stress relaxation modulus increased, the crosslinking network structure of HTPB coating became denser and the degree of cross-linking increased. At the initial aging stage, the pre-strain will destroy the crosslinking network structure of HTPB coating to a certain extent. With the increase of aging time, the effect of pre-strain will gradually weaken and the influence of aging on materials will gradually increase. The correlations between the stress relaxation model considering the molecular chains and the test results were more than 0.9950, which can accurately describe the stress relaxation modulus of HTPB coating during the pre-strain thermal aging process.     

多传感器多机动目标跟踪方法研究进展

讨论了多传感器多机动目标的研究现状,分析了几种跟踪滤波器的性能,着重探讨了交互多模型(IMM)算法的发展状况和应用。同时还研究了多传感器跟踪多机动目标过程中的数据关联方法。最后指出,寻求采用自适应变结构的IMM算法,研究模型切换过程中算法的过渡性能,以及在数据关联中引入混沌、遗传算法等智能控制方法,将是未来多传感器多机动目标研究的方向。     

空气动力和姿控发动机推力复合控制的弹体数学模型建立

建立了空气动力和姿控发动机推力复合控制弹体的数学模型,为理论弹道和控制弹道的计算提供了参考;同时采用小扰动法推导了俯仰通道和滚动通道的简化模型,为空气动力和姿控发动机推力复合控制系统进行初步设计提供了依据。     

激光防空武器系统作战效能研究

激光防空武器系统是一种新型的高技术多指标综合武器系统,其作战效能评估即是研究新型武器系统装备的主要依据,又是一件十分艰难的任务。依据WSEIAC提出的效能分析模型,建立了激光防空武器系统的ADC模型,对激光防空武器系统的作战效能作了研究,对其他武器的效能分析具有示范和借鉴作用。     

装备采购多目标激励模型研究

在将质量货币化从而实现激励目标测度统一的基础上,根据委托代理理论建立了委托人风险中性,代理人风险规避时的多目标激励数学模型,给出了激励系数的表达式,对激励系数与随机变量相关系数之间的关系进行了讨论。