基于虚拟检测函数下的IMM-UKF机动目标跟踪

为了有效提高对机动目标的跟踪效果,将无迹卡尔曼滤波(UKF)引入到交互多模型(IMM)算法框架内,加强状态估计精度;引入强跟踪滤波器(STF)到UKF算法中,避免对强机动目标的过大时间延迟和跟踪性能差的缺点;提出虚拟检测函数法,在跟踪过程中自适应调整"当前"统计模型的机动参数,加大模型集与目标真实运动模式匹配概率。仿真结果验证了改进算法的有效性。     

道路约束条件下的地面运动目标跟踪

有效使用道路信息能显著提高地面运动目标跟踪性能。基于卡尔曼滤波理论,提出了道路约束条件下的滤波方法。首先建立了描述道路网中路段的数学模型,给出了将目标分配于道路的定位算法;然后推导了道路约束条件下的过程噪声矩阵;提出了路段切换时状态修正公式;在道路约束最大后验概率估计准则下,根据道路参数修正状态与协方差。蒙特卡洛仿真结果证明了该算法的优越性能,且定量分析表明其计算量是可接受的。     

地面目标红外辐射特征测试研究

为研究地面目标红外辐射特征,进行了室内材料测试和外场地面目标测试,分析材料材质、太阳辐射、风速、空气温湿度、自身热源等因素对地面目标红外辐射特征的影响。结果表明:材料材质对红外辐射特征影响显著;冷态时,地面目标红外辐射特征主要受太阳辐射影响,其次是空气温度、材料热容量和风速;热态时,地面目标红外辐射特征主要受工作热源影响,其次是太阳辐射、空气温度、材料热容量和风速。在进行地面目标红外隐身设计时,应考虑太阳辐射、自身热源等因素的影响,并从结构设计和材料使用两方面着手。     

“What is dear to you?” Survey of beliefs regarding protection of critical infrastructure against terrorism

Up to the present, there is only very little research on how the population perceives terrorism and its threats, even though support from the population is crucial for effective counterterrorism. By eliciting beliefs and subjecting them to content analyses, six factors were found that determine the protection worthiness of a target in the people's view: the potential damage to “people,” “symbolism,” “economy,” “politics,” “nature,” and “image/publicity.” These empirically found factors are in line with factors specified by terrorist target selection models. They differ in the strength of their cognitive representation among participants and, thus, their subjective importance to the people. The first three factors are shared among all participants, whereas the latter ones could only be found in a part of the participant sample. People's judgments of the targets' protection worthiness differ substantially from their judgments of the targets' attractiveness to terrorists, even though the same factors seem to be involved. This study offers an insight into the people's mental model about protection worthiness of targets. Together with classical risk analysis and knowledge about terrorists, these results can form a basis for setting up a holistic scheme for critical infrastructure protection.     

基于改进截断正态概率密度模型的防发散多尺度卡尔曼滤波

借鉴对机动频率建模的思想,对机动目标的截断正态概率密度模型进行改进,提出了一种改进的截断正态概率密度模型(ICN模型),并将防发散算法与多尺度估计理论结合,用克服滤波器发散的S(k)算法对基本的多尺度估计进行机动检测和相应改进,得到单模型单传感器系统的防发散多尺度估计算法,旨在减小噪声影响,减小机动目标模型不准确带来的跟踪误差,改善跟踪效果。     

基于雷达网拓扑特征的雷达目标编群算法

为有效评估战场电磁态势和实施雷达网对抗,研究雷达目标编群算法十分必要。提出了一种基于拓扑特征分析的雷达目标编群算法,在分析雷达网拓扑结构及其特征基础上,利用拓扑特征实现雷达目标群的建立和更新,完成雷达目标编群。仿真实例表明算法具有可行性和有效性,为电磁态势评估和雷达网对抗奠定了基础。     

无人机小样本条件下遮挡和混淆目标识别方法

针对无人机对地目标识别过程中的小样本问题以及目标存在的遮挡和混淆情况,提出了一种融合自注意力机制的小样本目标识别模型。在利用元学习思想获取小样本学习能力的基础上,将自注意力机制学习目标内部各部分之间的上下文依赖关系引入模型,从而增强目标表征能力,以解决遮挡和混淆情况下有效特征不足的难题。为验证模型效果,通过对基准数据集和无人机航拍数据进一步加工,构建了遮挡和混淆目标数据集,设置了不同的遮挡程度和背景混淆率。通过在不同数据集上的验证,并与深度学习模型对比,证明提出的模型具有更高的学习效率和识别正确率。     

A pixel-level local contrast measure for infrared small target detection

Infrared (IR) small target detection is one of the key technologies of infrared search and track (IRST) systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure (PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously. With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker (RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.     

ESM量测间歇下雷达/ESM协同跟踪与辐射控制

为减少作战飞机目标跟踪过程中的雷达辐射,提出了一种ESM间歇量测情况下的机载雷达/ESM协同跟踪与辐射控制方法.采用基于IMM-EKF的雷达/ESM序贯滤波算法对目标进行滤波跟踪,利用跟踪过程中的预测协方差与预定门限进行比较控制雷达辐射,并给出了不同ESM间歇时间、控制门限与雷达辐射时间的关系.研究结论有助于提升作战飞机的隐蔽性和生存能力.     

基于最小模型集切换的变结构IMMPF算法

为提高对机动目标的跟踪精度,提出了一种新的基于最小模型集切换的变结构IMMPF跟踪算法,其中以"当前"统计模型为基础的不同最小模型集在不同时刻之间的切换实现了多模型的结构变换。当目标机动方式发生改变时,通过最小模型集的切换实现算法的滤波模型与目标实际机动方式的快速匹配,减小了目标机动的响应时间。通过仿真实验,与通用的IMM估计进行了比较,证明了算法的优越性。