GPS／INS制导系统中自适应天线阵列的干扰研究

目前GPS/INS制导已成为精确制导武器的核心.根据组合制导系统中自适应天线的特点,通过对微带自适应天线阵列的抗干扰性分析,着重研究了对GPS/INS组合制导系统中自适应天线阵列的分布式干扰.通过实验结果得出:要提高干扰效果,需要增加分布式干扰机数目、增大干扰机的运动速度和集中投放干扰源.     

火星着陆地形信息融合分析技术

文章以火星探测任务为背景,介绍了两种用于实时地形安全性评估的基于多敏感器的地形信息融合分析技术。这些技术综合考虑了影响着陆器安全着陆的多种地形特性信息,如地形粗糙度、坡度等,并且计算简单、处理速度快,能够满足火星着陆实时地形安全分析的要求。     

一种基于多模型算法的纯弹道式弹道落点预报方法

本文以落点预报技术在弹道目标预警中的应用为背景,主要解决在未知弹道系数情况下如     

Fourier变换的基本格式与PSD非参数估计

以传统Fourier变换为基础的非参数估计方法是振动工程研究中PSD估计的重要方法。文章以周期图法为例,研究Fourier变换基本格式的不同对PSD非参数估计结果的影响。首先介绍了Fourier变换常见的几种基本格式及其对应的PSD非参数估计计算公式;然后基于PSD的物理内涵,分析、证明多种不同形式的PSD估计公式的同时存在是一种人为误解,只有惟一的一种PSD估计结果才是具有典型物理意义的;最后给出了Fourier变换的一种通用格式及其PSD估计计算公式。     

基于UKF的异类传感器集中式融合算法

综合考虑航天器跟踪测量中速度和精度的要求,对异类传感器集中式融合问题进行了研究,提出了基于无迹卡尔曼滤波(UKF,Unscented Kalman Filter)和简化的分类数据压缩技术的非线性系统实时集中式融合算法.仿真表明新的算法融合性能优于基于扩展卡尔曼滤波(EKF,Extended Kalman Filter)和扩维技术的并行集中式融合算法.     

具有通信约束的分布式SOR多智能体轨迹估计算法

针对传统多智能体轨迹估计算法信息交换量大，计算量随群规模指数增长，可扩展性差等诸多不足，提出了一种基于超松弛迭代（SOR）的分布式多智能体轨迹估计算法，通过将最大似然（ML）准则下的轨迹估计转化为两级线性优化问题，并综合利用分布式超松弛迭代（Distributed SOR）和标记初始化方法，加快求解速度并简化信息交换流程，最终实现了多智能体位姿轨迹优化和协作定位。实验表明，所提的分布式方法能达到集中式算法的精度水平，在49个智能体规模条件下，位置估计误差小于0.15 m，姿态估计误差小于0.03°，且数据交换量仅到现有主流分布式方法DDF-SAM的0.06%，能很好用于大规模集群的场景。     

Using cross correlation to estimate Doppler frequency

Doppler frequency estimation with high accuracy is very important for precise orbit determination and scientific studies in deep space exploration. In this paper, we propose a new method which implements cross correlation of only received signals from one single station to estimate Doppler frequency. The algorithm is relatively simple and it can achieve high accuracy even when signal to noise ratio (SNR) is very low. Moreover, the accuracy can be further improved by implementing frequency compensation, especially when the frequency dynamic range is high. Simulations were performed and results proved the validity of this method. X-band observations on MEX (Mars Express) and Juno were performed by a 13 m telescope of Wuhan University, which was equipped by two back ends, i.e. CDAS (Chinese Data Acquisition System) and RSR (Radio Science Receiver). Raw data recorded by the CDAS were processed by using the proposed method, and the estimated frequencies were in good agreement with the real time frequency estimation values by the RSR. What’s more, the accuracy by using cross correlation was higher than the one of RSR.     

Track Association for Dynamic Target Tracking System Based on AP Algorithm

Track association of multi-target has been recognized as one of the key technologies in distributed multiple-sensor data fusion system,and its accuracy directly impacts on the performance of the whole tracking system.A multi-sensor data association is proposed based on aftinity propagation(AP)algorithm.The proposed method needs an initial similarity,a distance between any two points,as a parameter,therefore,the similarity matrix is calculated by track position,velocity and azimuth of track data.The approach can automatically obtain the optimal classification of uncertain target based on clustering validity index.Furthermore,the same kind of data are fused based on the variance of measured data and the fusion result can be taken as a new measured data of the target.Finally,the measured data are classified to a certain target based on the nearest neighbor ideas and its characteristics,then filtering and target tracking are conducted.The experimental results show that the proposed method can effectively achieve multi-sensor and multi-target track association.     

基于P2P的一种负载饱和避免技术研究

在点对点体系结构的分布式虚拟环境系统中,由于客户机节点的计算能力和带宽的异构性,以及发生在客户机程序之间交互信息量的不同,会导致一些客户机出现负载饱和。一台客户机的负载饱和不仅影响本机程序的运行,也会对周围其他的客户机的运行产生影响,这限制了分布式虚拟环境系统的性能。研究提出了一种在点对点体系结构的分布式虚拟环境系统中避免客户机负载饱和的技术,试验结果显示了所提出的方法有效地改进了系统的性能。     

Bass模型参数估计方法研究综述

详细介绍了新产品扩散Bass模型及其各种参数估计方法.模型的参数估计是影响模型准确性的一个重要方面,不同的参数估计方法,会使模型拟含结果相差很大,本文在对以往Bass模型参数估计方法进行分析评述的基础上,介绍了一种新的模型参数估计方法一蚁群算法,通过比较分析,认为蚁群算法将是一种更好的Bass模型参数估计方法.