As-IPDA算法的天波超视距雷达目标跟踪研究

天波超视距雷达(OTHR)具有低数据率、低检测概率和低量测精度特征对目标跟踪提出挑战.针对OTHR在低检测概率下跟踪目标存在失跟率高的问题,将As-IPDA算法应用到OTHR目标跟踪中,通过大量的仿真实例验证了As-IPDA算法在超视距雷达目标跟踪应用中的可行性,并分析了平滑步长、航迹存在性转移参数、目标检测概率对算法性能的影响,给出了算法参数选择建议,为工程应用提供理论参考.     

机动目标一维距离像RAT法线性化补偿

研究了机动目标宽带线性调频脉冲回波全去斜率信号模型,根据速度和加速度的调频频谱展宽特点,提出了机动目标宽带一维距离像线性化调频回波模型,给出了Radon模糊图转换(RAT)法线性参数估计与运动补偿方法,并进一步分析了测速和测距误差.仿真实验验证了RAT法一维距离像线性化参数估计与补偿,表明该方法很好地解决了运动参数未知情况下机动目标的一维距离像频谱展宽问题.     

Adjacency‐based local top‐down search method for finding maximal efficient faces in multiple objective linear programming

It is well‐known that the efficient set of a multiobjective linear programming (MOLP) problem can be represented as a union of the maximal efficient faces of the feasible region. In this paper, we propose a method for finding all maximal efficient faces for an MOLP. The new method is based on a condition that all efficient vertices (short for the efficient extreme points and rays) for the MOLP have been found and it relies on the adjacency, affine independence and convexity results of efficient sets. The method uses a local top‐down search strategy to determine maximal efficient faces incident to every efficient vertex for finding maximal efficient faces of an MOLP problem. To our knowledge, the proposed method is the first top‐down search method that uses the adjacency property of the efficient set to find all maximal efficient faces. We discuss this and other advantages and disadvantages of the algorithm. We also discuss some computational experience we have had with our computer code for implementing the algorithm. This computational experience involved solving several MOLP problems with the code.     

采用瞬态球状热斗篷方法的浅层地下目标红外隐身技术

由于浅层地下目标与背景土壤的热物性不同,影响了整个区域表面的温度场分布,容易被敌方探测系统发现并击毁。针对这一问题,考虑太阳辐射、天空辐射以及风速的影响,建立了埋藏地下目标的区域温度分布传热模型,揭示了不同时段埋藏地下目标对区域表面温度场的影响。在变换热力学的基础上,通过坐标变换的方法,推导出球状瞬态热斗篷的导热系数的通解表达式。根据等效介质理论,对设计的热物性参数进行均质化,并通过数值实验方法验证了基于热斗篷地下目标红外隐身技术的可行性。     

基于IMM滤波器的纯方位机动目标跟踪

针对无源纯方位跟踪中目标机动的问题,提出了一种基于交互式多模型的目标跟踪算法。该算法用伪量测变换估计器(PLE)将纯方位跟踪中非线性观测模型线性化,避免了计算雅克比行列式。机动目标跟踪中通过实时调整模型匹配概率,提高了滤波器对状态变化的跟踪能力。同时该算法实时修正观测噪声协方差,消除目标远离基阵时观测噪声对目标定位的影响。最后通过与MGEKF进行比较,Monte Carlo仿真结果验证了该算法的优越性。     

导航精度对某型电视制导无人攻击机攻击性能影响

针对电视制导无人机的作战使用方式,分析了影响其攻击性能的因素;建立了导航精度与攻击无人机捕获目标概率之间的关系;基于捷联惯导的误差分析,对无人机中制导末段的导航精度进行了计算。构建了对无人攻击机目标捕获概率进行仿真计算的方案,建立了方案航迹,对其进行了中制导精度分析和目标捕获概率计算,结果表明导航精度和捕获概率直接相关。     

Neighborhood search heuristics for selecting hierarchically well‐formulated subsets in polynomial regression

The importance of subset selection in multiple regression has been recognized for more than 40 years and, not surprisingly, a variety of exact and heuristic procedures have been proposed for choosing subsets of variables. In the case of polynomial regression, the subset selection problem is complicated by two issues: (1) the substantial growth in the number of candidate predictors, and (2) the desire to obtain hierarchically well‐formulated subsets that facilitate proper interpretation of the regression parameter estimates. The first of these issues creates the need for heuristic methods that can provide solutions in reasonable computation time; whereas the second requires innovative neighborhood search approaches that accommodate the hierarchical constraints. We developed tabu search and variable neighborhood search heuristics for subset selection in polynomial regression. These heuristics are applied to a classic data set from the literature and, subsequently, evaluated in a simulation study using synthetic data sets. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于禁忌退火算法的巡航导弹航迹规划

针对巡航导弹航迹规划这个复杂的优化问题,一个禁忌退火混合优化算法被提出.首先,该算法是以基本模拟退火算法为基础.其次,为了加快该模拟退火算法的收敛速度,在恶化解的接受判断过程中,增加了一定动态的约束条件.最后,为了使最优解能够跳出局部最优的陷阱,使用了一个动态的禁忌表.仿真结果验证了该禁忌退火混合优化算法能够取得目标函数更优的航迹规划路径,从而有效提高巡航导弹的作战效能.     

LFM脉冲雷达距离维快速搜索处理算法

针对脉冲雷达近距离目标遮挡问题,从理论上分析了雷达最小作用距离不受限于脉冲宽度.在此基础上,以Chirp脉冲为例,提出了一种适合远近距离全程目标的快速搜索处理算法.该算法只需发射一种宽脉冲波形,而不必根据距离的变化改变脉宽,从而有效缩短了搜索时间,大大提高了搜索效率.仿真结果表明了理论分析的正确性和算法的有效性.     

A search game taking account of attributes of searching resources

This article deals with a two‐person zero‐sum game called a search allocation game (SAG), in which a searcher and a target participate as players. The searcher distributes his searching resources in a search space to detect the target. The effect of resources lasts a certain period of time and extends to some areas at a distance from the resources' dropped points. On the other hand, the target moves around in the search space to evade the searcher. In the history of search games, there has been little research covering the durability and reachability of searching resources. This article proposes two linear programming formulations to solve the SAG with durable and reachable resources, and at the same time provide an optimal strategy of distributing searching resources for the searcher and an optimal moving strategy for the target. Using examples, we will analyze the influences of two attributes of resources on optimal strategies. © 2007 Wiley Periodicals, Inc. Naval Research Logistics 2008