军用飞行器航迹规划综述

介绍了军用飞行器航迹规划的基本概念，航迹规划与任务规划的关系，国内外研究现状，存在的问题，论述了航迹规划的基本要求，如导航要求，突防要求，飞行器性能要求及战略和战术要求，最后分析了航迹规划需要解决的威胁建模，航迹规划算法和轨迹跟踪控制等关键技术。     

直11型机可靠性初步评估

本文根据直11型机外场故障信息对直11型机的故障进行了分析,建立了直11型机的可靠性增长模型,对该机的可靠性进行了初步评估。     

一种基于无线信号辅助的室内无死角定位算法

针对传统惯性导航系统定位误差随时间积累的问题,提出了一种基于无线信号辅助定位的室内无死角定位算法。该算法首先利用加速度计、陀螺仪、磁力计和气压计等传感器数据实现三维定位,然后利用无线信号对惯导定位中的位置偏差进行实时校正,再通过航向最优估计算法对航向误差进行修正,在位置和航向上增强惯导系统的实用性。利用实验室自主研发的微惯性测量单元固定在腰部脊椎位置进行实验验证,结果显示基于无线信号辅助的室内无死角定位算法精度达到1%以内,与纯惯导技术相比,能够提供更持久和准确的三维位置信息。     

Regression model for civil aero-engine gas path parameter deviation based on deep domain-adaptation with Res-BP neural network

The variations in gas path parameter deviations can fully reflect the healthy state of aero-engine gas path components and units; therefore, airlines usually take them as key parameters for monitoring the aero-engine gas path performance state and conducting fault diagnosis. In the past, the airlines could not obtain deviations autonomously. At present, a data-driven method based on an aero-engine dataset with a large sample size can be utilized to obtain the deviations. However, it is still difficult to utilize aero-engine datasets with small sample sizes to establish regression models for deviations based on deep neural networks. To obtain monitoring autonomy of each aero-engine model, it is crucial to transfer and reuse the relevant knowledge of deviation modelling learned from different aero-engine models. This paper adopts the Residual-Back Propagation Neural Network (Res-BPNN) to deeply extract high-level features and stacks multi-layer Multi-Kernel Maximum Mean Discrepancy (MK-MMD) adaptation layers to map the extracted high-level features to the Reproduce Kernel Hilbert Space (RKHS) for discrepancy measurement. To further reduce the distribution discrepancy of each aero-engine model, the method of maximizing domain-confusion loss based on an adversarial mechanism is introduced to make the features learned from different domains as close as possible, and then the learned features can be confused. Through the above methods, domain-invariant features can be extracted, and the optimal adaptation effect can be achieved. Finally, the effectiveness of the proposed method is verified by using cruise data from different civil aero-engine models and compared with other transfer learning algorithms.     

Command filtered sliding mode trajectory tracking control for unmanned airships based on RBFNN approximation

This paper presents two sliding mode controllers to address the trajectory tracking problem of unmanned airships in the presence of unknown wind disturbance. The sliding mode controller proposed first is designed by a fast power rate reaching law(FPRRL). The disturbance is compensated by a radial basis function neural network (RBFNN). To avoid the aggressive adaptation, the controller is augmented by a command filter. The controller provides good robustness and tracking performance with no chattering under the hypothesis of ideal wind field. However, serious chattering occurs when simulation is performed under discontinuous wind field. To simulate the wind in practice, the wind field employed in the simulation is generated by the combination of a constant field and white noise. The controller is improved subsequently with an extended model to suppress the chattering induced by the white noise. The enhanced controller manipulates the derivation of system input, thus attenuating the chattering. Stability analysis shows that both controllers drive the tracking error into a controllable small region near zero. Simulations are provided to validate the performance of the proposed controllers under different wind hypothesis.     

基于AHP-Entropy 综合权重法的航空四站装备保障安全评价

针对航空四站装备保障安全评价问题,提出了基于层次分析法和熵权法的综合权重模糊评价模型。在构 建航空四站装备保障安全评价指标体系的基础上,综合利用层次分析法、熵权法的优点,改进了权重确立方法。该 方法将影响因素的主观性与客观性相结合,得出各指标综合权重。通过模糊综合评价法对某航空四站装备保障实 例分析,结果表明该权重确立法客观合理,可为航空四站装备保障风险控制提供判断依据。     

一种WSN虚拟多路径可靠路由协议

针对无线传感器网络中的数据传输不可靠问题,提出虚拟多路径路由协议,该协议将路由优化和数据传输结合在一起,按需建立可行路径集合,在数据传输的过程中实时采集分组的累计传输次数,通过对累计传输次数均值的区间估计,评估各路径的质量,识别并淘汰质量显著低的路径,根据网络实时链路质量动态的进行路由优化.在NS2平台上进行仿真,结果表明该协议能够适应带宽资源紧缺、链路不可靠且动态变化的无线传感器网络,在能量效率、分组递交率方面优于典型的路由优化和使用相分离的协议AODV_ETX.     

一种深空探测器自主天文导航新方法及其可观测性分析

天文导航是一种适用于深空探测器的完全自主的导航方法.与传统的直接利用天体观测信息进行滤波的方法不同,针对深空探测器,提出了一种首先利用天文观测信息通过几何解算得到一个初步的定位结果,再结合轨道动力学方程利用多模自适应(MM)滤波方法对初步结果进行再处理的自主天文导航新方法.仿真计算的结果表明,该方法可以明显提高导航定位精度,同时从可观测性和可观测度的角度,分析了应用该方法提高导航定位精度的原因和机理.     

基于数据压缩的多传感器多假设算法

为解决集中式多传感器系统中多目标跟踪问题,提出了一种新的多传感器多目标算法.提出的算法首先应用经典分配规则对每个传感器送来的观测数据进行排列组合,然后对每个组合中各量测点进行概率加权以获得一个等效量测点,最后根据每个等效量测点产生的互联假设计算其互联概率并获得融合中心的状态估计.给出了该算法与已有集中式多传感器联合概率数据互联算法的仿真比较,仿真结果表明该算法的跟踪性能在探测概率降低的跟踪环境下表现得更为优越.      

一种基于二元估计与粒子滤波的故障预测算法

假设对象系统的故障演化过程可以由一个含有未知缓变参数的状态空间模型加以描述,则故障预测问题就可以转化为一个在已知当前系统信息的条件下,对系统未来某一时刻的状态变量的估计问题.针对该问题的求解提出了一种基于二元估计和粒子滤波的故障预测算法.算法的实施分为两个主要阶段:在状态估计阶段,采用两个并联的粒子滤波器迭代估计当前时刻对象系统故障演化模型状态和未知参数的后验分布.在状态预测阶段,对当前时刻故障演化模型状态的后验分布进行迭代采样,以采样样本粒子来近似估计未来时刻的状态变量的先验分布密度.在上述计算结果的基础上,结合相应的故障判据,算法采用计算对象系统未来时刻故障概率的方法预测其剩余使用寿命.仿真实验中将本文提出的算法与基于联合估计的故障预测算法进行对比,实验结果证明了所提算法的有效性.