CNC数控系统控制软件

本文分析了数控机床控制系统,由硬件NC(Numerical Contro1)向CNC(ComputerNumerical Control)转变时进给速度下降的问题,阐述了解决此问题的一种方法——二次插补方法。指出CNC数控系统是个多重中断系统,论述了将数控的工作按其重要的程度、实时性的高低,安排在不同的优先级,使整个系统协调工作的思想。     

一种TASIMM-UKF导弹状态估计方法

为了提高对机动导弹状态估计的精度和速度,提出了一种三轴分离IMM-UKF(TASIMM-UKF)滤波算法。将导弹运动状态按坐标轴方向进行三轴分离,并基于CV,CA和CJ模型集,采用无迹卡尔曼滤波器并行估计导弹三轴状态信息,有效地解决了导弹不同运动轴间的模型竞争问题。仿真结果表明,该方法能有效提高状态估计精度,缩短了估计时间,对复杂大机动目标状态估计具有良好的性能。     

平台摇摆对卡尔曼滤波跟踪精度的影响

通过建立目标相对运动坐标系和目标相对运动观测模型,研究了在平台摇摆影响下,跟踪系统观测到的目标运动状态的变化。在分析捷联垂直基准补偿原理的基础上建立了捷联垂直基准平台摇摆角补偿模型,建立的模型结合捷联垂直基准系统的测量能力对其补偿算法进行了理论推导,使模型适用于实际捷联垂直基准系统。通过建立模型以及仿真研究了平台摇摆作用下卡尔曼滤波跟踪精度的变化,指出了摆造成卡尔曼滤波跟踪精度降低甚至离散的主要原因在于模型误差增大。设计仿真实验验证了结论的正确性,为进一步改进跟踪手段提供了理论参考。     

Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

Real-time object tracking via least squares transformation in spatial and Fourier domains for unmanned aerial vehicles

This paper addresses the problem of real-time object tracking for unmanned aerial vehicles. We consider the task of object tracking as a classification problem. Training a good classifier always needs a huge number of samples, which is always time-consuming and not suitable for realtime applications. In this paper, we transform the large-scale least-squares problem in the spatial domain to a series of small-scale least-squares problems with constraints in the Fourier domain using the correlation filter technique. Then, this problem is efficiently solved by two stages. In the first stage, a fast method based on recursive least squares is used to solve the correlation filter problem without constraints in the Fourier domain. In the second stage, a weight matrix is constructed to prune the solution attained in the first stage to approach the constraints in the spatial domain. Then, the pruned classifier is used for tracking. To evaluate proposed tracker's performance, comprehensive experiments are conducted on challenging aerial sequences in the UAV123 dataset. Experimental results demonstrate that proposed approach achieves a state-ofthe-art tracking performance in aerial sequences and operates at a mean speed of beyond 40 frames/s. For further analysis of proposed tracker's robustness, extensive experiments are also performed on recent benchmarks OTB50, OTB100, and VOT2016.     

基于MSP430点光源跟踪系统设计

提出了一种基于MSP430的点光源跟踪的具体设计方案,并对设计方案的硬件组成、程序设计、调试进行了介绍,实验证明,所设计的光源自跟踪系统有较强的适应能力,反应迅速,灵活性大。     

某靶用型无人机发动机空中停车故障分析

针对某新型靶机出现的发动机空中停车故障,对测控站记录数据进行分析,发现了转速采集系统和ECU控制系统存在的缺陷,并提出了解决措施。     

飞机大部件自动对接同步调姿方法

提出了飞机大部件自动对接同步调姿方法,实现了大部件调姿基准点的连续自动跟踪测量和位姿连续调整.在此基础上开发了集测量场构建、大部件位姿解算和调整等功能于一体的大部件自动对接集成控制软件,并在ARJ21飞机翼身自动对接现场进行了应用试验,结果证明该方法能有效完成飞机翼身自动对接过程,提高测量和对接效率.     

基于过渡工作过程的航空发动机气路分析方法

为对发动机机动性能的退化程度进行估计,开展了基于过渡工作过程的气路分析研究。针对气路传感器数目较少的情况,采用序列工作点方法对大量的健康参数进行分析,在增加可用信息量的同时,降低了由多工作点方法的平均效应引入的参数估计系统误差。为解决发动机大偏差性能退化健康参数估计中的计算收敛性问题,提出了间接递归牛顿-拉夫逊法强化非支配分类差分进化算法。针对某型双轴分排涡扇发动机的气路分析结果表明：采用本文所提出的方法能够在气路传感器数目有限的条件下,利用发动机过渡态数据实现对大偏差范围内大量健康参数的高效、准确估计。     

基于气压高度辅助的机载自主完好性监测算法

卫星接收机自主完好性监测是指根据用户接收机的多余观测值监测用户定位结果的完好性,其目的是在导航过程中检测出发生故障的卫星,并保障导航定位精度。针对卫星接收机自主完好性监测算法可用性不足的问题,结合机载实际导航系统配置,提出了一种基于气压高度表辅助的机载自主完好性监测算法。综合利用卫星导航系统及气压高度表观测信息,建立联合系统的观测模型,推导了基于多解分离的完好性监测及保护级别计算方法。仿真结果表明,相比于传统的接收机自主完好性监测算法,该算法在可见星为5颗时仍能识别故障卫星。该算法具有更好的故障检测能力及可用性,能有效提高卫星导航系统的完好性监测性能,从而保证卫星导航系统的精度和可靠性。