一种新的机动目标模型及其自适应跟踪算法

针对机动目标跟踪问题,在截断正态概率密度模型的基础上,通过目标机动状况与相邻采样时刻间位置估计量变化之间的函数关系实现噪声方差自适应调整,提出了一种新的自适应滤波算法——基于截断正态概率密度模型修正的自适应滤波算法。计算机仿真结果表明,该算法在跟踪机动目标时,具有良好的跟踪性能,并极大地改善了跟踪非机动目标的能力。     

一种基于LMS的时域相干累积算法研究

为了克服低信噪比条件下传统的自适应滤波算法抑制高斯噪声效果差的缺点,提出了基于最小均方(LMS)的时域相干累积新算法。计算机仿真结果表明,该算法具有良好的抑制高斯噪声的性能,对于低信噪比下信号的增强效果明显优于传统的自适应滤波算法。     

自适应过滤法在火灾发展趋势预测中的应用

分析了1993~2003年的火灾统计数据,应用自适应过滤模型预测了火灾发展趋势。结果表明:自适应过滤模型适于火灾趋势预测分析,在消防监督工作中具有广阔的应用前景。     

基于磁通门/GPS组合的车辆导航系统滤波技术

给出了基于磁通门/GPS组合导航系统的硬件结构图,并应用卡尔曼滤波和方差自适应滤波算法分别对GPS、磁通门单独导航定位系统进行了分散滤波,最后应用联合卡尔曼滤波器对GPS和磁通门信息进行了信息融合.并且通过实际跑车实验,验证了滤波对导航系统随机误差消除和定位精度提高的有效性.     

数字化扩频接收机的自适应抗干扰滤波方案研究

讨论了自适应抗干扰滤波在最小频移键控的直接序列扩频(DS-MSK)数字化接收机中的应用问题,对非线性滤波加以改进,提出了部分解扩非线性滤波(PDNF)结构,将快速更新子带自适应滤波(FRSAF)算法用于PDNF结构以提高收敛速度。结合FRSAF算法的PDNF自适应抗干扰滤波方案在收敛速度、稳健性和输出信噪比等方面明显优于结合LMS算法的传统非线性抗干扰滤波方案,仿真结果验证了上述结论。     

几种UWB-SAR窄带干扰抑制方法的分析和比较

SAR(Synthetic Aperture Radar)信号处理窄带干扰抑制技术是SAR抗干扰技术的重要内容。对3种UWB-SAR(Ultra-W ideBand Synthetic Aperture Radar)窄带干扰抑制方法———陷波滤波法、AR模型参数化干扰抑制法以及小波包分析自适应干扰抑制法进行了分析,利用自行开发的成像软件,对SAR理想点目标和实录数据进行干扰抑制仿真实验,从定性和定量的角度对3种方法的干扰抑制效果作了比较。     

多传感器参数融合研究

防空导弹武器系统为了适应“网络中心战”,对多传感器参数融合进行了研究。给出了同时间点参数融合的加权最小二乘法与不同时间点参数融合的Kalman综合滤波法。对于各方法的性能,不仅进行了简要的理论分析,还给出了仿真实验的数据结果。理论分析与仿真实验都证明了这2种方法具有优异性能。     

一种面向移动Agent的多任务并行计算模型及算法

介绍了一种面向移动Agent的并行计算模型,给出了采用十标度策略解决任务排序,采用满射策略解决任务映射的算法。该模型允许多个计算任务在异构主机构成的分布式环境下同时进行计算,并且通过算法优化,降低移动Agent之间的通信成本,减少网络流量。     

增强路由器安全性的一种措施

路由器是军用电子信息系统的关键互联设备,提高路由器自身的安全性非常必要。首先对路由器涉及到的安全问题作了较为详细地分析,然后给出一种增强路由器安全性的技术措施。该措施重点处理终点包对路由器的威胁,将入侵检测模块与数据包过滤模块进行联动,通过入侵预防、入侵时的检测和响应、入侵后的快速分析与恢复等三个环节,提高路由器抗攻击的能力。最后探讨了该措施对路由器性能的影响。     

Parallel machine scheduling with eligibility constraints: A composite dispatching rule to minimize total weighted tardiness

We study a parallel machine scheduling problem, where a job j can only be processed on a specific subset of machines M_j, and the M_j subsets of the n jobs are nested. We develop a two‐phase heuristic for minimizing the total weighted tardiness subject to the machine eligibility constraints. In the first phase, we compute the factors and statistics that characterize a problem instance. In the second phase, we propose a new composite dispatching rule, the Apparent Tardiness Cost with Flexibility considerations (ATCF) rule, which is governed by several scaling parameters of which the values are determined by the factors obtained in the first phase. The ATCF rule is a generalization of the well‐known ATC rule which is very widely used in practice. We further discuss how to improve the dispatching rule using some simple but powerful properties without requiring additional computation time, and the improvement is quite satisfactory. We apply the Sequential Uniform Design Method to design our experiments and conduct an extensive computational study, and we perform tests on the performance of the ATCF rule using a real data set from a large hospital in China. We further compare its performance with that of the classical ATC rule. We also compare the schedules improved by the ATCF rule with what we believe are Near Optimal schedules generated by a general search procedure. The computational results show that especially with a low due date tightness, the ATCF rule performs significantly better than the well‐known ATC rule generating much improved schedules that are close to the Near Optimal schedules. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 249–267, 2017