KGTLIR:An Air Target Intention Recognition Model Based on Knowledge Graph and Deep Learning

As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.

An Air Defense Weapon Target Assignment Method Based on Multi-Objective Artificial Bee Colony Algorithm

With the advancement of combat equipment technology and combat concepts,new requirements have been put forward for air defense operations during a group target attack.To achieve high-efficiency and lowloss defensive operations,a reasonable air defense weapon assignment strategy is a key step.In this paper,a multi-objective and multi-constraints weapon target assignment(WTA)model is established that aims to minimize the defensive resource loss,minimize total weapon consumption,and minimize the target residual effectiveness.An optimization framework of air defense weapon mission scheduling based on the multiobjective artificial bee colony(MOABC)algorithm is proposed.The solution for point-to-point saturated attack targets at different operational scales is achieved by encoding the nectar with real numbers.Simulations are performed for an imagined air defense scenario,where air defense weapons are saturated.The non-dominated solution sets are obtained by the MOABC algorithm to meet the operational demand.In the case where there are more weapons than targets,more diverse assignment schemes can be selected.According to the inverse generation distance(IGD)index,the convergence and diversity for the solutions of the non-dominated sorting genetic algorithm III(NSGA-III)algorithm and the MOABC algorithm are compared and analyzed.The results prove that the MOABC algorithm has better convergence and the solutions are more evenly distributed among the solution space.

Air target recognition method against ISRJ for radio frequency proximity sensors using chaotic stream encryption

The interrupted-sampling repeater jamming(ISRJ)can cause false targets to the radio-frequency proximity sensors(RFPSs),resulting in a serious decline in the target detection capability of the RFPS.This article proposes a recognition method for RFPSs to identify the false targets caused by ISRJ.The proposed method is realized by assigning a unique identity(ID)to each RFPS,and each ID is a periodically and chaotically encrypted in every pulse period.The processing technique of the received signal is divided into ranging and ID decryption.In the ranging part,a high-resolution range profile(HRRP)can be obtained by performing pulse compression with the binary chaotic sequences.To suppress the noise,the singular value decomposition(SVD)is applied in the preprocessing.Regarding ID decryption,targets and ISRJ can be recognized through the encryption and decryption processes,which are controlled by random keys.An adaptability analysis conducted in terms of the peak-to-side lobe ratio(PSLR)and bit error rate(BER)indicates that the proposed method performs well within a 70-k Hz Doppler shift.A simulation and experimental results show that the proposed method achieves extremely stable target and ISRJ recognition accuracies at different signal-to-noise ratios(SNRs)and jamming-to-signal ratios(JSRs).

Optimizing air quality and health Co-benefits of mitigation technologies in China: An integrated assessment

Carbon mitigation technologies lead to air quality improvement and health co-benefits,while the practical effects of the technologies are dependent on the energy composition,technological advancements,and economic development.In China,mitigation technologies such as end-of-pipe treatment,renewable energy adoption,carbon capture and storage(CCS),and sector electrification demonstrate significant promise in meeting carbon reduction targets.However,the optimization of these technologies for maximum co-benefits remains unclear.Here,we employ an integrated assessment model(AIM/enduse,CAM-chem,IMED|HEL)to analyze air quality shifts and their corresponding health and economic impacts at the provincial level in China within the two-degree target.Our findings reveal that a combination of end-of-pipe technology,renewable energy utilization,and electrification yields the most promising results in air quality improvement,with a reduction of fine particulate matter(PM2.5)by−34.6μg m^(−3) and ozone by−18.3 ppb in 2050 compared to the reference scenario.In contrast,CCS technology demonstrates comparatively modest improvements in air quality(−9.4μg m^(−3) for PM2.5 and−2.4 ppb for ozone)and cumulative premature deaths reduction(−3.4 million from 2010 to 2050)compared to the end-of-pipe scenario.Notably,densely populated regions such as Henan,Hebei,Shandong,and Sichuan experience the most health and economic benefits.This study aims to project effective future mitigation technologies and climate policies on air quality improvement and carbon mitigation.Furthermore,it seeks to delineate detailed provincial-level air pollution control strategies,offering valuable guidance for policymakers and stakeholders in pursuing sustainable and health-conscious environmental management.

An air cavity method for increasing the underwater acoustic targets strength of corner reflector

In order to improve the underwater acoustic target strength of comer reflectors,according to the principle of acoustic impedance mismatch of the boundary layer,the method of using air cavity to increase the underwater acoustic target strength of corner reflectors is proposed.The acoustic reflection coefficients of underwater air layer and single layer metal sheet are calculated and compared.The results show that the reflection coefficient of single layer metal sheet is greatly affected by frequency and incidence angle,and the reflection coefficient of air layer in water is large and little affected by frequency and incidence angle.On this basis,a new kind of airfilled cavity corner reflector is designed.The acoustic scattering characteristics of underwater airfilled cavity comer reflector are calculated cumulatively,and the results are compared with the monolayer metal sheet corner reflector.The simulation results show that the acoustic reflection effect of the airfilled cavity corner reflector is better.In order to verify the correctness of the method,the test was carried out in the silencing tank.The experimental results show that the simulation results are in good agreement with the experimental results,and the airfilled cavity can improve on acoustic reflection performance of the underwater corner reflector.

Full Digital Smart Fuze on Air Target

The intelligent fuzing is a kind of perfect way to optimize detonation location.The fuze can autonomously configure the warhead detonation mode to optimize the desired effects against the target.For the air target,the fuze can sense the impact in the impact mode then detonate the warhead on impact,otherwise,it will operate in the proximity mode and detonate at a closest approach to the target.The anti-jamming ability is also added on fuze＇s full digital signal processing platform.The method for burst point＇s controlling is analyzed and the digital intelligent fuze system based on system on programmable chip（SOPC） is designed.

Air Target Fuzzy Pattern Recognition Threat-Judgment Model

Threat-judgment is a complicated fuzzy inference problem. Up to now no relevant unified theory and measur-ing standard have been developed. It is very difficult to establish a threat-judgment model with high reliability in the airdefense system for the naval warships. Air target threat level judgment is an important component in naval warship com-bat command decision-making systems. According to the threat level judgment of air targets during the air defense of sin-gle naval warship, a fuzzy pattern recognition model for judging the threat from air targets is established. Then an algo-rithm for identifying the parameters in the model is presented. The model has an adaptive feature and can dynamicallyupdate its parameters according to the state change of the attacking targets and the environment. The method presentedhere can be used for the air defense system threat judgment in the naval warships.

Hybrid hierarchical trajectory planning for a fixed-wing UCAV performing air-to-surface multi-target attack

This paper considers the problem of generating a flight trajectory for a single fixed-wing unmanned combat aerial vehicle （UCAV） performing an air-to-surface multi-target attack （A/SMTA） mission using satellite-guided bombs. First, this problem is formulated as a variant of the traveling salesman problem （TSP）, called the dynamic-constrained TSP with neighborhoods （DCT- SPN）. Then, a hierarchical hybrid approach, which partitions the planning algorithm into a roadmap planning layer and an optimal control layer, is proposed to solve the DCTSPN. In the roadmap planning layer, a novel algorithm based on an updatable proba- bilistic roadmap （PRM） is presented, which operates by randomly sampling a finite set of vehicle states from continuous state space in order to reduce the complicated trajectory planning problem to planning on a finite directed graph. In the optimal control layer, a collision-free state-to-state trajectory planner based on the Gauss pseudospectral method is developed, which can generate both dynamically feasible and optimal flight trajectories. The entire process of solving a DCTSPN consists of two phases. First, in the offline preprocessing phase, the algorithm constructs a PRM, and then converts the original problem into a standard asymmet- ric TSP （ATSP）. Second, in the online querying phase, the costs of directed edges in PRM are updated first, and a fast heuristic searching algorithm is then used to solve the ATSP. Numerical experiments indicate that the algorithm proposed in this paper can generate both feasible and near-optimal solutions quickly for online purposes.

Three-Dimensional Discrete Observability Analysis for Air-to-Air Missile Target Tracking

The interception information of infrared（ IR）-guided air-to-air missiles（ AAM） is mainly estimated only using the basic bearing measurements. In order to intercept highly maneuverable targets,it is essential to study the system observability to improve the target tracking system performance.The uniqueness of this paper is that the observability analysis is derived based on a discrete three-dimensional （3D） system model. During the maneuvering scenario,the system is approximated by a segment-by-segment system. The relationship between missile-target motion and observability is given by direct and dual approaches. Meanwhile sufficient observability conditions are derived. Moreover,a numerical simulation is conducted and an alternate method is provided to reinforce the proposed observability analysis results.

基于深度强化学习的舰船导弹目标分配方法

针对对抗环境下的海上舰船防空反导导弹目标分配问题,本文提出了一种融合注意力机制的深度强化学习算法.首先,构建了舰船多类型导弹目标分配模型,并结合目标多波次拦截特点将问题建模为马尔可夫决策过程.接着,基于编码器–解码器框架搭建强化学习策略网络,融合多头注意力机制对目标进行编码,并在解码中结合整体目标和单个目标编码信息实现舰船可靠的导弹目标分配.最后,对导弹目标分配收益、分配时效以及策略网络训练过程进行了仿真实验.实验结果表明,本文方法能生成高收益的导弹目标分配方案,相较于对比算法的大规模决策计算速度提高10%~94%,同时其策略网络能够快速稳定收敛.

天空地一体化多目标跟踪算法研究综述

为实现全时全域“泛在连接”,构建天空地一体化网络已成为国家重大需求,而基于天空地一体化网络下跨域协同系统进行多目标跟踪是其中一个重要的发展方向,其在军民用领域都极具应用价值。本文详细阐述了天空地一体化网络背景下多目标跟踪方法研究进展。首先,介绍了天空地一体化跨域协同多目标跟踪的研究背景与意义。其次,从基于视觉的多目标跟踪、基于模型的多目标跟踪和基于多模态融合的多目标跟踪三个方面概述了当前的代表性研究方法:在基于视觉的多目标跟踪算法方面,介绍了单摄像头和多摄像头融合的多目标跟踪方法;对于基于模型的多目标跟踪,先介绍了单传感器多目标跟踪方法,以及在多种复杂场景下的改进,然后介绍了多传感器融合方法;在基于多模态信息融合的目标跟踪方面,在对多传感器时空配准方法和有代表性的多模态信息融合方法介绍的基础上,概括了基于多模态融合的多目标跟踪算法。最后探讨了当前存在的问题和未来发展方向:无论基于视觉的还是基于模型的多目标跟踪方法都有不少问题有待解决,特别是两种方法的结合值得深入研究;在面临复杂干扰时,基于多传感器信息融合的多目标跟踪由于能实现信息的互补,成为未来的主流发展方向;此外,跨域协同系统,由于能利用更多的资源和信息,其多目标跟踪问题研究极具价值,不过其中通信安全问题和多目标跟踪模型轻量化问题值得探讨。本文对从事目标跟踪及空天地一体化协同控制相关理论与技术研究的科研工作者具有重要参考价值。

基于双线性插值的单目标检测算法

针对已有算法对于空中小目标检测效果差、精度低、漏检等问题,提出一种基于双线性插值的单目标检测算法。对主干网络进行设计,再根据特征图的特点,使用不同的方法进行特征融合。在特征融合的过程中使用双线性插值算法进行上采样。对算法的先验框进行设计,使算法的先验框尺寸与数据集目标框尺寸更加契合。实验结果表明,提出算法的平均检测精度对比SSD提升了10.29%,算法计算量对比Faster-RCNN减少了82.18%。

空战目标轨迹预测技术研究综述

信息化空战对抗中,快速获取和有效利用对手信息的一方,能够准确地预测对手的运动轨迹,更加迅速地完成OODA循环,进而取得空战优势。本文研究空战目标轨迹预测技术,以时序变化特征为研究视角,分别对基于物理、机器学习和深度学习的轨迹预测技术开展分析和总结,进一步归纳物理因素、空战因素和交互因素等作为轨迹预测模型的输入,单模态轨迹、多模态轨迹和行为意图三类作为模型的输出,并对未来智能化空战中的目标轨迹预测技术进行展望。

基于机器视觉的小白杏热风干燥控制系统设计

设计了一种基于机器视觉的小白杏热风干燥控制系统,该系统使用计算机视觉技术,对小白杏进行检测和分类,并自动控制热风干燥过程中的温度、风速。系统采用基于神经网络的目标检测算法,对小白杏进行检测和分割,利用图像处理技术提取小白杏的特征,并使用YOLOv7对小白杏进行分类。通过调整热风干燥的温度、风速和时间等参数,实现了对小白杏干燥过程中的品质保护,可保持小白杏品质和口感,提升杏干经济价值,该系统具有一定的应用前景。

花椒热风-微波组合干燥失水特性研究

花椒热风干燥降速期水分含量低,水分扩散慢,导致热风干燥耗时长。为提高干燥效率,并通过热风与微波组合干燥,分别进行热风干燥、微波干燥和热风-微波组合干燥实验,探究不同干燥参数对花椒失水特性的影响,以确定合理的干燥转换临界点和最优组合干燥模型,并将傅里叶准则数(F_(0))引入Fick第二扩散定律方程,求解有效水分扩散系数(D_(eff))。研究结果表明:热风和微波单独干燥时,升高风温风速和增加微波功率均有利于缩短干燥时间;热风-微波组合干燥花椒时,热风段转微波段的最佳目标含水率即为热风干燥的临界点含水率(65%(w.b)),且高热风温度和高微波功率均可使微波干燥段获得高失水速率;热风-微波组合干燥花椒热风段和微波段对应的最优模型分别为Wang and Singh模型和Page模型,D_(eff)范围分别为1.908×10^(-9)~3.547×10^(-9)m^(2)/s和1.883×10^(-8)~3.321×10^(-8)m^(2)/s。热风-微波组合干燥方式能够显著提高干燥效率,促进花椒内部水分扩散,干燥模型可为优化干燥工艺和设计干燥设备提供理论依据。

流体动力式喷水室撞击流喷嘴研究进展综述

文章阐述了流体动力式喷水室撞击流喷嘴的研发历程。以研发时间为顺序,介绍了PX离心式喷嘴、撞击流对喷式喷嘴、撞击流靶式喷嘴,详细分析了各喷嘴的产生背景、结构特点、雾化原理与性能参数,旨在为后续相关研究提供参考。

基于防空目标探测与跟踪的雷达资源管理技术研究综述

雷达资源管理是一项运用优化运筹理论挖掘雷达系统性能边界,通过对系统资源的高效分配和合理调度,实现系统的优化运行,并显著增强系统性能表现的综合性技术。随着机械扫描雷达、相控阵雷达以及多输入多输出(Multiple-input multiple-output,MIMO)雷达技术的持续革新,雷达资源管理技术也在不断深化拓展,以满足日益复杂的目标探测与跟踪需求。鉴于军事威胁的不断加剧和装备技术的迅猛发展,为实现我军未来“网络中心战”的对抗模式,对防空反导武器预警探测装备的资源管理技术研究显得尤为重要。本文聚焦基于防空目标检测、跟踪的信息感知的雷达资源管理技术进行综述,深入剖析与总结现有文献以及研究成果:首先,本文从宏观角度系统概述了雷达资源管理的概念、管理要素组成以及优化策略求解方法。在此基础上,根据雷达系统架构将雷达资源管理研究内容划分为单站雷达资源管理和多站雷达资源管理,并分别对相控阵雷达、集中式MIMO雷达、分布式MIMO雷达以及组网雷达的资源管理研究现状进行梳理和讨论。最后,探讨当前研究中存在的问题和挑战,并对未来基于防空信息目标感知的雷达资源管理技术研究的发展趋势进行展望。期望本文能够为防空反导预警探测装备领域的研究学者提供有价值的参考,推动雷达资源管理技术的持续创新与进步。

HEURISTIC PARTICLE SWARM OPTIMIZATION ALGORITHM FOR AIR COMBAT DECISION-MAKING ON CMTA

Combining the heuristic algorithm （HA） developed based on the specific knowledge of the cooperative multiple target attack （CMTA） tactics and the particle swarm optimization （PSO）, a heuristic particle swarm optimization （HPSO） algorithm is proposed to solve the decision-making （DM） problem. HA facilitates to search the local optimum in the neighborhood of a solution, while the PSO algorithm tends to explore the search space for possible solutions. Combining the advantages of HA and PSO, HPSO algorithms can find out the global optimum quickly and efficiently. It obtains the DM solution by seeking for the optimal assignment of missiles of friendly fighter aircrafts （FAs） to hostile FAs. Simulation results show that the proposed algorithm is superior to the general PSO algorithm and two GA based algorithms in searching for the best solution to the DM problem.

近距空中支援中无人机目标分配问题研究

利用无人机实施近距空中支援作战是当前研究的重点,需针对复杂战场环境对实行多目标火力打击的无人机进行路径优化与目标分配。综合考虑无人机飞行高度、不同武器挂载、目标类型及各项指标、威胁区威胁代价、作战时间代价等因素,构建目标毁伤综合指标提高非对称打击效能,设置威胁区安全阈值提高路径有效性分析,采取自适应权重粒子群协同优化算法求解单无人机单目标航迹总代价,采取0-1规划法求解多无人机对多目标的不平衡任务分配方案,为近距空中支援任务中多无人机对多目标的分配提供决策支撑。

基于自报位航迹数据的海空目标数据集

目标航迹由一段时间内的点迹组成,按照时间顺序排列,是一种典型的时间序列。航迹数据蕴含着目标的运动特征,在目标跟踪、识别、关联等方向的研究中,实验设计需要大量的航迹数据作为支撑。当前,一部分研究在对实际环境和传感器分析的基础上,探索实现数据的仿真流程,构建与真实世界尽可能相符的仿真数据,并利用仿真数据对方法进行验证;另一部分研究直接采集真实数据,通过对真实数据进行积累和预处理,构建真实数据集进行实验。仿真数据缺乏说服力,难以检验所提方法在真实环境下的性能,而真实数据鲜有公开,增加了研究者获取数据的难度,造成数据闭塞。因此有必要构建并公开专业规范的航迹数据集,为弥补航迹数据集缺少的问题,本文构建并公开了基于自报位航迹数据的海空目标数据集。该数据集包含海面目标航迹数据和空中目标航迹数据两部分,其中海面目标航迹数据来自于船舶自动识别系统数据,空中目标航迹数据来自于广播式自动相关监视数据。通过对两种类型的数据进行长期积累,针对数据特点建立起数据预处理及数据集构建流程,为海空目标跟踪、识别、关联等算法提供了数据支撑。同时本文进一步给出了识别评价指标并利用基线算法进行了实验与分析,结果表明了该数据集的有效性。