多传感器融合状态估计方法综述

随着传感器网络技术的发展，多传感器融合状态估计凭借其鲁棒性、灵活性、可扩展性以及便于故障检测等优点，长期受到国内外学者的广泛关注，并取得了大量研究成果。数据融合的方法为融合状态估计奠定了理论基础，也是早期研究的主要方向，从20世纪70年代到20世纪末，相继发展出了集中式和分散式滤波架构及相应算法。无线通信技术的成熟以及一致性算法的出现使得分布式状态估计的研究进入了快车道，自2005年以来，大量基于一致性的分布式滤波算法被提出，其中不乏实用的经典方法和优秀的开创性方法。旨在梳理多传感器融合状态估计的发展，探究从数据融合到分布式滤波的内在联系，并对一些经典方法进行了总结。     

基于多DSP的机载SAR距离徙动校正实现方法

针对机载合成孔径雷达(SAR)数据量大、运算复杂、实时性能要求高等问题，提出了一种基于多片多核DSP并行的方式实现机载SAR距离徙动校正的方法。重点介绍实现过程中的片间及片内并行和同步处理、数据交互、数据分配，距离徙动校正的距离向脉冲压缩和惯导补偿，以及多普勒中心估计实现的具体步骤，利用点仿真和实测数据验证了该方法的有效性，并提出优化模块，进一步提高运算的实时性。     

合成孔径雷达射频干扰抑制技术进展及展望

射频干扰(RFI)是影响合成孔径雷达精确遥感的一个难点问题,严重阻碍了原始回波的采集、成像和后续解译过程。本文对适用于合成孔径雷达系统的RFI抑制技术进行了综述研究。首先分析了典型的星载和地面RFI源以及其对合成孔径雷达系统的影响,给出了典型RFI类型的信号模型和实测数据示例;然后系统地介绍了抑制RFI的先进信号处理技术,并从适用性的角度讨论了每种方法的优缺点;最后从认知、综合和自适应的角度探讨了未来干扰抑制技术的发展趋势与展望。     

固定翼无人机编队的启发分布式模型预测控制

针对无人机编队飞行控制中队形保持、路径规划、重构、防撞等多重功能需求,采用启发型分布式模型预测控制框架,将需求转化为多目标优化问题中的代价函数与相容性约束求解,实现了对无人机编队飞行的一体化控制.同时,采用分阶段式的轨迹规划算法,融合模型预测轨迹规划与多项式轨迹规划,利用多项式轨迹系数实现高效的邻居轨迹信息交互,从而增大了模型预测控制的预测范围,并降低了规划控制过程中的计算量与通信量.最后,通过9架无人机的协同避障编队仿真,证明了该方法的有效性.     

Distributed satellite autonomous navigation using X-ray pulsars

Distributed X-ray pulsar-based navigation (DXNAV) is an effective method to realize earth-orbit satellite positioning under weak pulsar signal conditions. In this paper, we propose a new DXNAV method based on multiple information fusion. The DXNAV system principle and the pulse phase estimate Cramér-Rao lower bound are deduced. To suppress the calculation complexity and the error source, the X-ray pulsar photon time-of-arrival detected by each satellite is equivalently converted to the leading satellite directly using the inter-satellite link ranging and starlight angular distance measurement. A high precision estimate model of the pulse phase is built using pulsar standard profile, observed profile, and star-geocentric angular distance from distributed satellites. The estimated pulse phase is real-time supplied to the navigation system, which is established in the form of a deviation equation. The two-stage Kalman filter is designed to estimate the pulse phase in profile histogram bin step and the leader position in real-time step. Compared separately with the maximum likelihood phase estimate method and the celestial navigation method using only the star-geocentric angular distance, the simulation analysis shows that the estimation precisions of position and velocity are improved by 29% and 25%.     

Design of hybrid-electric aircraft with fault-tolerance considerations

The potential benefits of hybrid-electric or all-electric propulsion have led to a growing interest in this topic over the past decade. Preliminary design of propulsion systems and innovative configurations has been extensively discussed in literature, but steps towards higher levels of technological readiness, optimisation algorithms based on reliable weight estimation and simulation-based mission analysis are required. This paper focuses on the integration of a method for evaluating the lateral-directional controllability of an aircraft within a design chain that integrates aero-propulsive interactions, accurate modelling of the fuel system, and mid-fidelity estimation of the structural weight. Furthermore, the present work proposes a strategy for powerplant management in scenarios with an inoperative chain element. Benefits of hybrid-electric propulsion on the design of the vertical tail plane are evaluated involving the analysis of multiple failure scenarios and certification requirements. The proposed application concerns a commuter aircraft.     

OGSRN: Optical-guided super-resolution network for SAR image

Although Convolutional Neural Networks(CNNs) have significantly improved the development of image Super-Resolution(SR) technology in recent years, the existing SR methods for SAR image with large scale factors have rarely been studied due to technical difficulty. A more efficient method is to obtain comprehensive information to guide the SAR image reconstruction.Indeed, the co-registered High-Resolution(HR) optical image has been successfully applied to enhance the quality of SAR image due to it...     

一种基于遗传算法的最小熵自聚焦方法

自聚焦算法是获得高质量合成孔径雷达SAR(Synthetic Aperture Radar)图像的重要步骤.针对复杂成像场景和复杂运动误差SAR自聚焦问题,提出一种基于遗传算法的最小熵自聚焦方法.方法 通过高阶多项式函数拟合相位误差,以图像熵为代价函数,利用遗传算法最小化代价函数进而估计出相位误差,尤其适合于成像场景没...     

非死锁合同网协议驱动的多机分布式时序任务分配

针对多无人机协同任务分配的时序约束问题，提出了基于非死锁合同网协议(DF CNP)的分布式时序任务分配方法，从理论上避免任务死锁，提升分配结果最优性。定义了局部信息条件下时序任务死锁判据，通过检测时序任务图环路状态与顶点可达性，判定分配方案的全局死锁状态，保证分配结果的可行性。定制了最近邻-深度优先混合搜索算法，在合同网排序过程中优先选择最近邻任务，并结合死锁判据递归回溯，在分布式架构下并行生成满足死锁约束的任务排序方案，提升分配结果的最优性。仿真对比结果表明：相比于非死锁遗传算法(TB GA)，DF CNP在求解效率方面具有显著优势；与耦合约束一致性束算法(CBBA TCC)相比，DF CNP结果最优性明显提升。