基于退化信息融合理论的可靠性预测研究

传统的可靠性评估方法一般基于失效寿命数据,而目前对于高可靠长寿命的电子产品,很难通过加速试验获得其失效寿命时间。为解决这一矛盾,将性能退化理论、信息融合技术与传统可靠性评估方法相结合,提出基于退化信息融合理论的可靠性预测的新方法,并应用某型雷达24V/2A稳压电源板的加速性能退化试验进行验证,结果表明方法用于高可靠长寿命电子产品的可靠性评估是正确有效的。     

Novel moderate transformation of fuzzy membership function into basic belief assignment

In information fusion, the uncertain information from different sources might be modeled with different theoretical frameworks. When one needs to fuse the uncertain information represented by different uncertainty theories, constructing the transformation between different frameworks is crucial. Various transformations of a Fuzzy Membership Function (FMF) into a Basic Belief Assignment (BBA) have been proposed, where the transformations based on uncertainty maximization and minimization can determine the BBA without preselecting the focal elements. However, these two transformations that based on uncertainty optimization emphasize the extreme cases of uncertainty. To avoid extreme attitudinal bias, a trade-off or moderate BBA with the uncertainty degree between the minimal and maximal ones is more preferred. In this paper, two moderate transformations of an FMF into a trade-off BBA are proposed. One is the weighted average based transformation and the other is the optimization-based transformation with weighting mechanism, where the weighting factor can be user-specified or determined with some prior information. The rationality and effectiveness of our transformations are verified through numerical examples and classification examples.     

Timeliness optimization of unmanned aerial vehicle lossy communications for internet-of-things

Information freshness is a key factor for Internet-of-Things(Io T) to make appropriate decisions and operations. This paper proposes an analytical framework for evaluating the timeliness performance of the Io T system based on Unmanned Aerial Vehicle(UAV) lossy communications.The performance analysis consists of the outage probability analysis and the Age-of-Information(Ao I) analysis with outages. To begin with, we solve a lossy coding problem formulated from the UAV communication system, and d...     

A multi-satellite co-tracking method for a single space target based on adaptive distributed spherical simplex information-weighted consensus filter

A multi-satellite co-tracking method for a single non-cooperative target is proposed to extend the arc of observation as well as to improve the accuracy of tracking. Firstly, the motion of the target is considered to be affected by J2 perturbation, and the model of multi-satellite co-tracking a single space target is designed with only measured angles. Then, a multi-satellite co-tracking method for a single space target based on an adaptive distributed spherical simplex information-weighted consensus filter (ADSSICF) is proposed. The spherical simplex is used to reduce the computational cost of the information filter, and to improve the efficiency of tracking. The angle-only measurement equation is linearized by the statistical linear regression method, and linearization errors are compensated for by updating measurement noise. By designing an adaptive consensus algorithm, only a small number of iterations are needed to achieve network consensus, to improve the convergence speed of the consensus algorithm, and prove the stability of ADSSICF. Finally, a simulation of four low-orbit satellites tracking a single space target is established. The focus of this paper is on the real-time performance and tracking accuracy of the multi-satellite co-tracking a single space target with angle-only based on ADSSICF. The performance of ADSSICF is verified from three indicators: the consensus and convergence of algorithm, the accuracy of state estimation.     

运载火箭姿态控制多速率陀螺融合方法

针对柔性火箭姿态测量中弹性信号会严重影响姿控系统设计和稳定性的问题，提出基于遗传算法的速率陀螺融合方法。首先，以降低姿控回路摆角指令传递函数的弹性峰值为目标，提出多速率陀螺融合方法的目标函数;其次，将多速率陀螺融合方法转化为多约束非线性规划问题，采用遗传算法求解多速率陀螺融合方法;最后，研究多速率陀螺融合方法对火箭姿态控制回路弹性信号的影响，以及对火箭控制器性能的影响。仿真结果表明:多速率陀螺融合方法可以有效减弱火箭姿态控制回路中的弹性信号，提高火箭控制器的性能，以增强火箭姿控系统的稳定性，降低火箭控制器设计难度。     

基于交互融合的高精度图像融合算法的研究

针对可见光和SAR图像融合，提出了一种基于跨模态差分感知和注意力机制的交互融合（TDPAM Fusion）算法，能有效保留可见光图像中的纹理结构和SAR图像的细节信息。首先，采用跨模态差分感知融合（Cross-Modal Differential Perception Fusion，CMDAF）模块提取图像的互补信息，避免真值缺失并提高融合精度。其次，通过坐标注意力机制（Coordinate Attention，CA）提高特征提取的准确性和效率，增强语义信息的集成。最后通过交互融合算法（Interactive Fusion Module，IFM）将特征自适应融合。设计了相应的大型基准数据集，用于网络模型的训练和测试。实验结果表明：TDPAM Fusion融合算法可以获得包含清晰SAR信息的高质量可见光图像。此外，融合算法将互信息（Mutual Information，MI）、空间频率（Spatial Frequency，SF）、视觉保真度（Visual Fidelity，VIF）和相关系数（Correlation Coefficient，CC）等关键指标，分别提高了约6.41％、10.36％、14.25％和4.74％。     

Combination of classifiers with incomplete frames of discernment

The methods for combining multiple classifiers based on belief functions require to work with a common and complete(closed) Frame of Discernment(Fo D) on which the belief functions are defined before making their combination. This theoretical requirement is however difficult to satisfy in practice because some abnormal(or unknown) objects that do not belong to any predefined class of the Fo D can appear in real classification applications. The classifiers learnt using different attributes inform...     

惯性/视觉/激光雷达SLAM技术综述CSCD

同时定位与建图(SLAM)技术已广泛应用于各类自主移动平台中,其中视觉SLAM和激光雷达SLAM是两种主要的SLAM技术方案。然而,视觉SLAM系统易受视觉环境变化的影响,而激光雷达SLAM系统则在结构单一等环境中会出现精度退化甚至失效的情况。随着智能移动平台应用场景的不断拓展,对SLAM系统的精度和鲁棒性等提出了更高要求,将多种具有互补性的传感器进行融合是提升SLAM系统性能的有效途径。据此,聚焦惯性/视觉/激光雷达多传感器融合SLAM技术,从多传感器标定和多源数据融合两个主要方面进行综述,最后对多传感器融合SLAM技术的发展趋势进行了展望。     

An information-volume-based distance measure for decision-making

D-S evidence theory, as a general framework for reasoning with uncertainty, allows combining pieces of evidence from different information sources to derive a degree of belief function that is a type of fuzzy measure. However, the mass assignments given by unknown information sources are disordered. How to measure the difference between the mass assignments has aroused people’s interest. In this paper, inspired by the information volume, a novel distance-based measure is proposed to measure the difference between mass assignments. The method can refine the uncertain information given by experts and compare the refined information to obtain the difference between mass assignments. At the same time, it is verified that the measure not only meets the properties of distance, but also proves the superiority of the proposed Information Volume Distance (IVD) through simulation experiments. Meanwhile, in the process of information fusion, the reliability of each source could be quantified through IVD. Therefore, based on IVD, a new multi-source information algorithm is proposed to solve the problem of multi-source information fusion. Moreover, algorithm is applied to decision-making problem and compare with other methods to verify the effectiveness.     

基于改进式YOLOv2的红外图像目标识别方法

针对智能化导引头信息处理算法设计验证需求，本文对多类型目标、海陆空背景辐射特性数据进一步挖掘，提出引入深度学习算法应用于外场红外数据二次分析挖掘的方法。选择采集得到的包括车、船、无人机(UAVs)、客机等类型的红外数据，针对红外图像与可见光图像不同的成像特性，利用改进式YOLOv2红外目标检测与分类算法，融合多级特征，增加一个重组特征图，实现对红外弱小目标智能化快速分类研究，对提取的海量视频库中的目标红外辐射特征进行分类整理。