基于点集合并的修正Hough变换TBD算法

在低信噪比条件下,基于Hough变换的检测前跟踪算法是进行强杂波背景下目标航迹检测的一种手段。本文针对Hough变换后一个目标产生多条可能航迹以及航迹内可能存在杂波点的问题,提出了一种基于能量最大点和点集合并的修正Hough变换检测前跟踪算法。该算法利用量测点时序、能量信息及目标速度先验信息对Hough变换后点迹进行关联和剔除,能够有效的对目标原始航迹进行回溯。针对高斯噪声背景下的飞行目标,仿真结果表明该算法能够对微弱目标进行有效检测,在目标数目、杂波密度、信噪比发生变化的条件下仍能保持较高的检测概率。     

海杂波背景下小目标检测及其运动信息的提取

介绍了在基于Hough变换的检测前跟踪算法检测海杂波背景下的低可观测目标的基础上,将动态规划方法引入其中,从每一条“特征直线”所包含的数据点迹中提取最可能构成目标点迹的数据点的方法。仿真结果表明,将Hough变换与基于动态规划的航迹搜索相结合,能够提高低信噪比条件下的目标检测概率,并能比较准确地提取出目标点迹。然后对提取出来的目标点迹进行Kalman滤波,以估计目标的速度,从而为后续的检测与跟踪提供比较准确的目标信息。     

基于邻帧差分近邻反相特征的红外运动点目标检测算法

基于运动点目标在邻帧差分图像中所具有的近邻反相特征,即运动点目标的两个位置相邻近、灰度值一正一负,提出一种在复杂背景下,基于红外序列图像的运动点目标检测算法.本算法利用该特征在邻帧差分图像中检测反相点对,进而构造反相点对矢量图,最后依据累积反相点对矢量图中多矢量首位相接的连续性检测出运动的点目标.文中给出并证明应用本算法能以概率1检测到运动点目标的收敛性定理.对典型复杂背景下10幅1000帧图像的仿真结果表明,当信噪比大于或等于1.5时,可以有效检测出运动点目标.     

单脉冲跟踪雷达多目标检测算法性能分析

对2种检测单脉冲雷达主波束内是否存在2个不可区分目标的算法进行了推广,将其应用到波束内可能存在N个不可区分的目标,并仿真了波束内存在3个目标时的检测性能。仿真表明,在总信噪比相同时,3个目标的检测概率不一定大于2个目标的检测概率,处于方位向上间距最大的2个目标的信噪比对整个检测概率影响较大。     

基于动态规划的低可观测目标检测与跟踪

动态规划算法用于检测与跟踪低可观测的运动目标,它是一种“检测置前跟踪”技术,在检测到目标的同时得到目标航迹。通过仿真,给出了动态规划算法的处理结果并分析了动态规划算法的性能。结果表明该算法在低信噪比时可以观察到较好的性能,但是当信噪比进一步下降时,其性能会迅速下降。     

使用电场传感器阵列的水下运动目标检测与参数估计

研究了基于电场传感器阵列的水下运动目标检测与参数估计方法。在背景噪声为高斯白噪声和目标作匀速直线运动的假设下,利用电场传感器阵列获取的船舶水下准静态电场空时特征,通过广义似然比检测和随机搜索寻优算法,可实现对海水中运动船舶的目标检测和参数估计。仿真试验结果表明:在信噪比大于0 dB时能够取得较好的估计精度;在信噪比低至10 dB时仍能有效检测目标。     

一种改进的直方图概率多假设多目标跟踪方法

直方图概率多假设跟踪（H-PMHT）方法及其变形泊松分布直方图概率多假设跟踪（P-HPMHT）方法的一个主要缺点是其量测模型仅考虑了背景杂波而没有考虑传感器噪声,从而导致在低信噪比条件下检测概率较低。针对这一问题,提出了一种带传感器噪声模型的H-PMHT方法,通过将传感器噪声引入量测模型,从而明显提高了对低信噪比目标的跟踪检测能力。该方法的计算量与目标数保持线性关系,仍然适用于目标数目较多的情况。仿真实验表明：该方法在误跟踪比率为1‰,信噪比为6 dB时,检测比率可提升近20%,信噪比为3 dB时,可提升近10%。     

基于自适应线谱增强的LOFAR浮标信号处理及Doppler-CPA定位方法

LOFAR浮标是一种被动全向浮标,用于对潜搜索的初始阶段。常规的LOFAR谱图对于小信噪比和有色背景噪声处理性能下降。文中采用自适应线谱增强技术将目标辐射中的线谱成分从背景噪声中分离出来进行LOFAR谱图分析,提高LOFAR浮标的检测性能。在LOFAR分析的基础上利用目标的多普勒信息,采用Doppler-CAP方法测算目标的速度和目标与浮标的距离,初步估算出目标的航迹。仿真结果表明,新的LOFAR浮标数据处理算法检测性能更好,能够得到目标与浮标最接近点的距离。     

一种舰载相控阵制导雷达驻留时间动态调度算法

为了解决舰载相控阵雷达的实时驻留问题,提出了一种新的相控阵雷达驻留时间调度算法。依据工作方式优先级和目标信噪比来设计调度准则。首先分析了构建舰载相控阵雷达模型所需要的各种理论模型,包括自由空间目标回波功率、干扰模型、目标检测模型。在此基础上,提出了雷达时间动态调度算法机制。最后根据建立的舰载多功能相控阵雷达模型分析驻留时间分配,目标信噪比检测的效能,仿真结果表明了该算法的合理性和有效性。     

红外弱小目标检测跟踪算法研究

首先对红外图像进行建模,然后在此基础上提出一套目标检测跟踪算法,给出了实验结果。实验结果表明,算法能够很好地完成对信噪比大于4目标的检测,同时算法具有多目标检测能力。当确定需要跟踪的目标以后,系统转入目标跟踪,进而完成对所关注目标的跟踪任务。     

基于自适应遗传BP算法神经网络数据融合的空中目标识别

空中目标识别是现代防空作战的重要研究内容。本文利用不同类型目标产生的多类型传感器的数据信息对目标进行识别。为了训练神经网络目标识别分类器，将遗传算法和BP算法相结合，提出了一种新的自适应遗传BP算法，利用这种神经网络来确定指标的权值。仿真试验结果表明，基于自适应遗传BP算法神经网络的识别是一种简单、可靠的目标识别方法，具有很好的目标识别效果。     

基于改进遗传算法的多无人机路径规划

对多无人机在动态环境下的路径规划问题进行了分析与建模,模型将无人机区分为就绪、工作、返航、失控4种状态;考虑了机群工作效率和威胁区域的生存概率,提出一种基于改进遗传算法的多无人机的路径规划方法。方法设计了新的编码、解码方法和具有明确物理意义的适应度评价函数,以加快实时的运算速度和提高运算精度。通过计算机仿真表明方法具有良好的多无人机动态路径规划能力。     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.     

天基对地打击武器空间机动过程分析

天基对地打击武器是一种新的战略威慑力量,与地基发射的武器相比具有自己独特的优势。首先通过对天基武器作战过程的分析,得出在轨机动是实现天基快速对地打击的关键的结论;而后建立了天基平台的轨道面机动与相位机动的数学模型。在上述研究的基础上,通过数学仿真分析了轨道机动对打击时间的影响,得到了一些有用的基本结论。     

Evaluation of the state and development of aerial targets for testing contemporary and promising arms systems

The results of evaluating the state and development of aerial targets designed for testing aircraft weapon, systems of air defense and combat crew training are presented. The basic types of aerial targets are examined using as an example existing ones and problems are posed to consider the necessity of creating new types of aerial targets for extending a range of FV types being simulated. The basic characteristics of aerial targets are separated and their classification is proposed.     

复杂背景下红外弱小运动目标检测的新方法

提出了一种用于检测不同类型复杂背景下红外弱小运动目标的新方法。该方法能够根据图像信息自动选择背景预测算子;同时,针对不同类型复杂背景中目标和背景特性的差异,提出了“局部小目标可辨识度”的概念,并定义了一种有效的方法将其量化。在此基础上,采用蒙特卡罗实验方法构造了一种新的阈值函数,实现了单帧目标的检测,然后采用移动加权管道滤波提取目标的运动轨迹。实验结果表明,该方法对不同类型复杂背景的红外弱小运动目标具有很好的检测性能。     

Simultaneous ISAR imaging of group targets flying in formation

This paper proposes a novel inverse synthetic aperture radar(ISAR) imaging method based on second-order keystone transform(KT) and Sandglass transform for group targets flying in a formation with constant accelerated rectilinear motion in the same radar beam. First, range curvature and range walk of each sub-target among group targets are corrected by the second-order KT combined with the quadratic phase term compensation. After range alignment, the signals in each range frequency cell can be modelled as multiple chirp signals and then the Sandglass transform is utilized to cross-range imaging, which transforms the time–frequency distribution of the signals in each range frequency cell into beelines parallel to the slow time axis simultaneously. Finally, cross-range profiles of group targets in each range frequency cell are obtained via a projection of the perk of every scatterer in the two-dimensional accumulation plane onto the frequency axis. The advantage of the proposed method is that it can align range profiles of each sub-target simultaneously and image cross-range profiles directly without separating the returned signals, which simplifies the operation procedure. Simulation results are used to demonstrate the effectiveness of the proposed method.     

Cooperative task assignment of multiple heterogeneous unmanned aerial vehicles using a modified genetic algorithm with multi-type genes

The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.     

高斯非平稳机动目标波达角模型及跟踪

在实际的跟踪情况中,由于环境条件、目标反射截面等因素的变化,回波信号的功率会随时间变化,即不满足通常阵列信号处理中对高斯信号作平稳性的假设。针对复杂运动条件下高斯非平稳目标的跟踪问题,提出了一种新的机动目标波达角(DOA)模型。该模型全面地刻画了高斯非平稳机动目标的动态,并将目标的DOA和信号功率作为状态变量进行了联合考虑,同时运用虚拟阵列的表示方法构建了相应的观测方程。对于建立的新模型,最后采用无迹卡尔曼滤波(UKF)的框架完成了整个跟踪算法。分析和仿真结果表明,当高斯非平稳机动目标之间存在长时间相互接近的情况时,新方法仍然可以获得较好的跟踪性能。     

基于深度图推理的卫星背板部件检测方法

在轨加注是一种典型的在轨服务操作,它对于降低空间运输成本和任务风险起着重要的作用,视觉感知系统可以感知操作任务周围环境并提供给控制系统。目前在轨加注依赖于人,在人员监控下完成或通过遥操作完成,缺乏自主性。本文围绕未来高自主性的基于深度强化学习的在轨加注方法,对基于深度学习的视觉感知方法展开了研究,针对基于深度学习的方法对相似实例的检测存在精确率低、对光照变化敏感等缺点,提出了基于深度图推理的卫星背板部件检测方法。提出的方法可以有效地检测复杂形状的目标,不依赖于手工设计的特征;提高了复杂光照环境下部件的检测正确率;可以有效区分外形相似的不同部件;其有效性在数学仿真和物理仿真中均得到了验证。