基于速度积分匹配的旋转调制惯导系统动基座对准方法

卫星导航信息辅助动基座对准过程中,速度噪声会影响对准精度和快速性,制约了旋转调制惯导角秒级高精度快速对准的实现.针对这一问题,提出了一种基于旋转调制惯导速度积分匹配的快速动基座对准方法,通过建立旋转调制惯导动基座对准误差方程和卡尔曼滤波观测模型,以消除动基座对准对载机特殊运动的要求.最后,在实验室静态环境和车载环境下,分别开展了速度积分匹配和速度十位置组合导航动基座对准仿真实验.仿真结果表明,提出的速度积分匹配方法具有误差估计量收敛速度快的特点,在对准精度不降低的情况下相对组合导航匹配方式能有效缩短动基座对准时间,并能基于旋转调制惯导取消动基座对准对载机的机动需求.     

基于多模特征融合的雷达干扰信号识别

传统制导雷达面临的新型有源干扰样式越来越复杂，雷达必须对各种干扰类型加以鉴别。传统的干扰识别方法仅对特定单一样式有效，通用性较差、泛化能力较弱，无法应对复杂多变的干扰对抗环境。因此，必须提出智能化更高、稳健性更强的普适干扰识别方法，提升制导武器抗干扰能力。为了提高干扰信号识别的准确率，研究了多模特征融合算法，并最终对时域、时频域、信息论特征进行融合以实现分类。首次将信息论中熵、相对熵、相对距离等概念引入到干扰信号分类这个应用场景中，通过仿真实验表明，能够有效对常见干扰进行有效识别，在较低干噪比下也有较好的识别准确率。     

基于ViBE与面向对象分类的视频卫星运动车辆检测

为了提高视频卫星对运动车辆的检测质量，在经典视觉背景提取器(ViBE)算法的基础上，结合遥感的面向对象分类技术，从提升正确检测运动目标数量和抑制虚假运动目标检测数量两个方面着手，提出了一种新的运动车辆检测方法（VOMVD）。首先通过优化ViBE模型参数，尽可能多地获取真实运动目标，但这在一定程度引入了许多的虚假目标。研究继而依据影像上地面小尺度运动目标和道路的依存关系，采用面向对象的分类方法，基于光谱、纹理、空间属性，构建了均值、标准差、卷积核内平均灰度值、卷积核内平均信息熵、面积、长度、紧密度、延伸度等8个特征，用于提取道路信息，以此掩膜ViBE提取的虚假运动目标和伪运动目标。结果表明，基于本研究提出的视频卫星运动目标检测方法较之三帧差分法、ViBE检测方法等，其精度有明显提升。在本研究中，三帧差分法、ViBE和VOMVD对运动目标的检测精度P分别为70.91%，61.49%和85.71%，召回率R分别为84.78%，98.91%和97.83%，F值分别为77.23%，75.83%和91.37%，有效提升了方法对运动目标的检测效果。     

Improving aircraft aerodynamic performance with bionic wing obtained by ice shape modulation

For Unmanned Aerial Vehicles (UAVs) with limited electrical power to achieve effectively anti-/de-icing at the leading edge of the wing, a strategy of ice shape modulation was proposed. Isolated simulated ice shape pieces printed by 3D printing technology are mounted on a NACA0012 finite wing model, and its lift/drag coefficients and suction-side velocity fields are measured by the six-component force balance and the Particle Imaging Velocimetry (PIV), respectively. The ratio of the spanwise length of a single ice shape piece to chord length and the spanwise length of the non-icing area between the two adjacent single ice shape pieces are defined as dimensionless ice shape length (w/c) and dimensionless modulation ratio (w/λ), respectively. The results indicate that for a fixed w/λ, the wing lift coefficient first increases and then drops with increasing w/c, and a peak value exists when w/c is between 0.1 and 0.2. The lower the w/λ is, the higher the wing lift coefficient will be. The periodical variation of the flow separation area along the spanwise direction is attributed on the one hand to the acceleration effect of the flow field in the non-icing area which reduces the separation area, and on the other hand to the cross-flow caused by the streamwise vortices from the non-icing area to the icing area which promotes the mixing of the flow field (similar to vortex generators). The obtained modulation law is verified through flight tests and provides guidance for the use of ice shape modulation scheme for UAVs that cannot be completely anti-/de-icing under severe weather conditions.     

旋转调制下的抗晃动干扰初始对准方法

针对晃动基座下的对准精度受限于惯性器件常值误差，提出了旋转调制下的抗晃动干扰初始对准方法。首先，分析了单轴连续旋转调制技术对常值误差的补偿机理，并在此基础上建立了晃动基座下的惯性器件输出模型;其次，详细推导了基于双重积分的惯性系粗对准算法，通过惯性坐标系下的姿态更新跟踪载体实际姿态变化消除了角晃动干扰，通过对比力进行双重积分克服了线振动影响;最后，在粗对准算法基础上，进一步建立了旋转调制下的系统状态方程和量测方程，通过反馈校正的卡尔曼滤波算法实现最优估计精对准。仿真结果表明:旋转调制下的抗晃动对准方法在克服晃动干扰的同时，能够解决对准精度受限问题，有效提高了初始对准精度。     

基于DJI精灵4多光谱版无人机的红树林精细分类

本文基于DJI（大疆）精灵4多光谱版无人机能够同时获取地表可见光照片和多光谱影像的特点，提出了使用摄影测量技术构建冠层高度模型（CHM）的方法，并结合多光谱影像应用于红树林分类。将上述方法应用于广东省湛江红树林国家级自然保护区高桥镇研究区，结果表明：基于无人机摄影测量技术构建的红树林CHM与多光谱影像结合后能够大幅提高红树林的分类精度，可替代传统的机载激光雷达数据；DJI精灵4多光谱版无人机数据获取效率高，能够实现高精度的红树林分类，在红树林监测业务工作中具有推广应用价值。     

Few-shot electromagnetic signal classification: A data union augmentation method

Deep learning has been fully verified and accepted in the field of electromagnetic signal classification. However, in many specific scenarios, such as radio resource management for aircraft communications, labeled data are difficult to obtain, which makes the best deep learning methods at present seem almost powerless, because these methods need a large amount of labeled data for training. When the training dataset is small, it is highly possible to fall into overfitting, which causes performance degradation of the deep neural network. For few-shot electromagnetic signal classification, data augmentation is one of the most intuitive countermeasures. In this work, a generative adversarial network based on the data augmentation method is proposed to achieve better classification performance for electromagnetic signals. Based on the similarity principle, a screening mechanism is established to obtain high-quality generated signals. Then, a data union augmentation algorithm is designed by introducing spatiotemporally flipped shapes of the signal. To verify the effectiveness of the proposed data augmentation algorithm, experiments are conducted on the RADIOML 2016.04C dataset and real-world ACARS dataset. The experimental results show that the proposed method significantly improves the performance of few-shot electromagnetic signal classification.     

First measurements of periodicities and anisotropies of cosmic ray flux observed with a water-Cherenkov detector at the Marambio Antarctic base

A new water-Cherenkov radiation detector, located at the Argentine Marambio Antarctic Base (64.24S-56.62 W), has been monitoring the variability of galactic cosmic ray (GCR) flux since 2019. One of the main aims is to provide experimental data necessary to study interplanetary transport of GCRs during transient events at different space/time scales. In this paper we present the detector and analyze observations made during one full year. After the analysis and correction of the GCR flux variability due to the atmospheric conditions (pressure and temperature), a study of the periodicities is performed in order to analyze modulations due to heliospheric phenomena. We can observe two periods: (a) 1 day, associated with the Earth’s rotation combined with the spatial anisotropy of the GCR flux; and (b) $～$ 30 days due to solar impact of stable solar structures combined with the rotation of the Sun. From a superposed epoch analysis, and considering the geomagnetic effects, the mean diurnal amplitude is $～$ 0.08% and the maximum flux is observed in $～$ 15 h local time (LT) direction in the interplanetary space. In such a way, we determine the capability of Neurus to observe anisotropies and other interplanetary modulations on the GCR flux arriving at the Earth.     

基于Turbo方法的乘积码脉冲位置迭代调制解调译码

脉冲位置调制（PPM）无线光通信系统易受到大气湍流影响，针对于此，将Turbo技术引入到PPM的解调和乘积码译码中。基于极大似然准则导出了PPM软检测解调方法，结合分组码的SISO译码，构建了检测解调和译码联合迭代的Turbo结构，推导了其迭代原理算法。仿真分析结果表明，误码性能可随迭代次数增加改善，其中，在大气闪烁指数0.1和误码率10-6条件下，迭代3~5次相比非迭代系统获得了0.8 dB以上的增益。     

基于冲突分类与消解的多智能体路径规划算法设计CSCD

多智能体路径规划应用广泛但求解困难。为更好地处理多智能体路径规划中的路径冲突问题,提高求解效率,将冲突进一步分类为相向顶点冲突和交叉顶点冲突,并提出了对应的消解方式。相向顶点冲突的消解方法采用提前添加约束的方式,避免在消解其冲突的过程中产生另一个可预见的冲突;交叉顶点冲突的消解方法采用寻找最佳等待时间的方式,在消解其冲突的同时消解其他存在的冲突。两种冲突消解方法均可减小约束树的规模,在一定程度上减少算法的计算量。并提出了基于冲突搜索算法的高层节点冲突搜索算法。实验结果表明,所提出的冲突分类及消解方式有效地减小了算法高层中约束树的规模,降低了算法计算量,并在智能体密集的环境下表现出更大的优势。