UAV Velocity Measurement for Ground Moving Target

To satisfy the demand of measuring the velocity of ground moving target through unmanned aerial vehicle(UAV)electro-optical platform,two velocity measurement methods are proposed.Firstly,a velocity measurement method based on target localization is derived,using the position difference between two points with the advantages of easy deployment and realization.Then a mathematical model for measuring target velocity is built and described by 15 variables,i.e.UAV velocity,UAV attitude angular rate,camera direction angular rate and so on.Moreover,the causes of velocity measurement error are analyzed and a formula is derived for calculating the measurement error.Finally,the simulation results show that angular rate error has a strong influence on the velocity measurement accuracy,especially the UAV pitch angular rate error,roll angular rate error and the camera angular altitude rate error,thus indicating the direction for improving velocity measurement precision.     

基于区间数灰色关联分析的测向能力评估研究

在现代战争中,如何快速、准确获取敌方通信辐射源的位置信息,是反辐射武器攻击和窃取敌方重要指挥节点情报信息中的关键问题.而如何选择测向能力较强的装备执行测向任务,保证在有限的时间内充分获取敌方辐射源的有效位置信息,又是把握战机的重要因素之一.针对测向装备性能指标区间描述模糊的情况,利用区间数灰色关联分析法对不同测向方式的...     

基于预处理和网格自适应的风力机翼型气动力计算

用预处理后的Navier-Stokes方程数值模拟低马赫数下风力机翼型的静态和动态绕流流动。为了提高计算的精度,运用了网格自适应技术:初始网格的流场计算收敛后,采用流场速度的紊乱度捕捉湍流区域;采用直接分裂初始父单元的H型网格加密方法对湍流区域进行局部加密。基于初始网格与自适应网格的计算结果与实验结果的对比表明,网格自适应方法提高了计算的精度。     

Sensitivity analyses of satellite propulsion components with their thermal modelling

Performing the sensitivity analyses of the contact conduction and the position of thermostat on the basis of the thermal model established, the study of thermal design is accomplished for the preparation of possible mechanical interface change of the satellite propulsion system depending on the satellite system design. A relatively simple thermal model is taken into consideration for the convenience of the analysis. A variety of the spacecraft bus voltages and the contact resistances are examined as well as the position of thermostat on propulsion components. As a consequence, even though the mechanical interface condition is changed on the same module, the successful thermal design could be achieved if we design the heater to have sufficiently large power with reference to the heritage value of contact resistance. Besides the reasonable performance on the thermal control is assured with the thermostat location errors, if the uncertainty in the position of thermostat is not quite large when assembling tank module.     

航空发动机维修技术进展与展望

航空发动机是为航空装备提供动力的装置,维修保障是保障发动机完成服役周期的重要阶段。随着航空发动机维修产业的不断发展,为满足未来大批量、高质量、高效率的维修需求,发动机维修技术也在不断提升和发展。本文简要介绍了航空发动机维修发展历史;从故障检查、整机清洗和整机装配三个方面综述了航空发动机整机维修技术的研究进展,从再制造发展、关键技术和技术开发流程三个方面阐述了航空发动机再制造进展;并对航空发动机维修和再制造技术的未来发展进行了展望。     

An improved multiple model GM-PHD filter for maneuvering target tracking

In this paper, an improved implementation of multiple model Gaussian mixture probability hypothesis density (MM-GM-PHD) filter is proposed. For maneuvering target tracking, based on joint distribution, the existing MM-GM-PHD filter is relatively complex. To simplify the filter, model conditioned distribution and model probability are used in the improved MM-GM-PHD filter. In the algorithm, every Gaussian components describing existing, birth and spawned targets are estimated by multiple model method. The final results of the Gaussian components are the fusion of multiple model estimations. The algorithm does not need to compute the joint PHD distribution and has a simpler computation procedure. Compared with single model GM-PHD, the algorithm gives more accurate estimation on the number and state of the targets. Compared with the existing MM-GM-PHD algorithm, it saves computation time by more than 30%. Moreover, it also outperforms the interacting multiple model joint probabilistic data association (IMMJPDA) filter in a relatively dense clutter environment.     

Feedback structure based entropy approach for multiple-model estimation

The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.