数字景象图的计算机模拟生成

数字景象图在飞行器末制导中起着关键作用。在特殊情形下，有必要用计算机模拟生成数字景象图。本文在分析数字景象图成象机理的基础上给出了一个基于数字高程图模拟生成数字景象图的框架，分别讨论了光照模型，大气模型，误差模型，坐标系和视点变换等关键步骤。文中给出了模拟生成的结果。     

基于哈特莱变换的快速图像模板匹配算法

去均值归一化模板互相关(ZNCC)是工程中应用最多的图像匹配算法,但过高的计算复杂度严重限制了其在实时系统中的应用.针对这一问题,提出了基于快速哈特莱变换的快速模板图像匹配算法,首先推导了该算法在哈特莱域的表达式,利用可分离的快速哈特莱变换对相关面进行高效率整体计算,然后在空间域对获取的相关面进行快速归一化处理和极值搜索,并通过空间换取时间和积分图的策略进一步加快算法的计算速度.对算法计算量的定量分析和仿真实验结果表明,算法计算效率高,并且可以完全重构,加速比与图像内容无关,综合性能全面优于现有算法,具有良好的工程应用前景.     

Inter-satellite links for satellite autonomous integrity monitoring

A new integrity monitoring mechanisms to be implemented on-board on a GNSS taking advantage of inter-satellite links has been introduced. This is based on accurate range and Doppler measurements not affected neither by atmospheric delays nor ground local degradation (multipath and interference). By a linear combination of the Inter-Satellite Links Observables, appropriate observables for both satellite orbits and clock monitoring are obtained and by the proposed algorithms it is possible to reduce the time-to-alarm and the probability of undetected satellite anomalies.     

某型飞机导航误差对CCD稳瞄系统目标搜索域的影响

分析了DG-1型多普勒／GPS组合导航系统，在不同工作方式下导航误差所引起的搜索方位角的误差；讨论了由于搜索方位角的变化引起的搜索域的变化。通过对机理的研究提出了解决办法。     

量子定位系统技术发展及其对导弹武器发展的影响

针对现有导航技术的不足,特别是天基卫星导航技术（如GPS）易受到干扰和破坏,美英两国相续进行了量子定位系统技术的研究。分析了量子定位系统产生的背景,阐述了量子定位系统的概念,对量子定位系统进行了分类,分析了其特点,重点梳理了量子定位系统的发展轨迹,继而分析了量子定位系统对导弹武器发展的影响,最后给出总结。     

靶场GNSS增强、监测与评估系统建设构想

针对靶场GNSS（全球导航卫星系统）增强、监测与评估的测量精度和可靠性保障、异常分析和电磁环境监测等复杂技术需求,明确了靶场GNSS增强、监测与评估的概念,分析了各类方法的特点,确定了以大范围基准站网为主干,采用广域差分增强和地面完好性通道监测满足提高测量精度和可靠性主要需求,采用车载信号监测和干扰监测一体化系统满足不同区域间发的异常分析和电磁环境监测需求的技术路线.设计了系统体系架构,重点分析了系统实时工作模式和数据处理流程,为系统建设提供了有益的参考.     

Design and simulation of ex-range gliding wing of high altitude air-launched autonomous underwater vehicles based on SIMULINK

 High altitude air-launched autonomous underwater vehicle (AL-AUV) is a new anti-submarine field, which is designed on the Lockheed Martin's high altitude anti-submarine warfare weapons concept (HAAWC) and conducts the basic aerodynamic feasibility in a series of wind tunnel trials. The AL-AUV is composed of a traditional torpedo-like AUV, an additional ex-range gliding wings unit and a descending parachute unit. In order to accurately and conveniently investigate the dynamic and static characteristic of high altitude AL-AUV, a simulation platform is established based on MATLAB/SIMULINK and an AUV 6DOF (Degree of Freedom) dynamic model. Executing the simulation platform for different wing's parameters and initial fixing angle, a set of AUV gliding data is generated. Analyzing the recorded simulation result, the velocity and pitch characteristics of AL-AUV deployed at varying wing areas and initial setting angle, the optimal wing area is selected for specific AUV model. Then the comparative simulations of AL-AUV with the selected wings are completed, which simulate the AUV gliding through idealized windless air environment and gliding with Dryden wind influence. The result indicates that the method of wing design and simulation with the simulation platform based on SIMULINK is accurately effective and suitable to be widely employed.     

Evaluation on real-time dynamic performance of BDS in PPP,RTK, and INS tightly aided modes

Since China’s BeiDou satellite navigation system (BDS) began to provide regional navigation service for Asia-Pacific region after 2012, more new generation BDS satellites have been launched to further expand BDS’s coverage to be global. In this contribution, precise positioning models based on BDS and the corresponding mathematical algorithms are presented in detail. Then, an evaluation on BDS’s real-time dynamic positioning and navigation performance is presented in Precise Point Positioning (PPP), Real-time Kinematic (RTK), Inertial Navigation System (INS) tightly aided PPP and RTK modes by processing a set of land-borne vehicle experiment data. Results indicate that BDS positioning Root Mean Square (RMS) in north, east, and vertical components are 2.0, 2.7, and 7.6?cm in RTK mode and 7.8, 14.7, and 24.8?cm in PPP mode, which are close to GPS positioning accuracy. Meanwhile, with the help of INS, about 38.8%, 67.5%, and 66.5% improvements can be obtained by using PPP/INS tight-integration mode. Such enhancements in RTK/INS tight-integration mode are 14.1%, 34.0%, and 41.9%. Moreover, the accuracy of velocimetry and attitude determination can be improved to be better than 1?cm/s and 0.1°, respectively. Besides, the continuity and reliability of BDS in both PPP and RTK modes can also be ameliorated significantly by INS during satellite signal missing periods.     

Cooperative task assignment of multi-UAV system

With the rapid development of Unmanned Aerial Vehicle (UAV) technology, one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment. Among the challenges in fully achieving autonomous control, Cooperative task assignment stands out as the key function. In this paper, we analyze the importance and difficulties of multi-UAV cooperative task assignment in characterizing scenarios and obtaining high-quality solutions. Furthermore, we present three promising directions for future research: Cooperative task assignment in a dynamic complex environment, in an unmanned-manned aircraft system and in a UAV swarm. Our goal is to provide a brief review of multi-UAV cooperative task assignment for readers to further explore.     

Deep reinforcement learning for six degree-of-freedom planetary landing

This work develops a deep reinforcement learning based approach for Six Degree-of-Freedom (DOF) planetary powered descent and landing. Future Mars missions will require advanced guidance, navigation, and control algorithms for the powered descent phase to target specific surface locations and achieve pinpoint accuracy (landing error ellipse <5 m radius). This requires both a navigation system capable of estimating the lander’s state in real-time and a guidance and control system that can map the estimated lander state to a commanded thrust for each lander engine. In this paper, we present a novel integrated guidance and control algorithm designed by applying the principles of reinforcement learning theory. The latter is used to learn a policy mapping the lander’s estimated state directly to a commanded thrust for each engine, resulting in accurate and almost fuel-optimal trajectories over a realistic deployment ellipse. Specifically, we use proximal policy optimization, a policy gradient method, to learn the policy. Another contribution of this paper is the use of different discount rates for terminal and shaping rewards, which significantly enhances optimization performance. We present simulation results demonstrating the guidance and control system’s performance in a 6-DOF simulation environment and demonstrate robustness to noise and system parameter uncertainty.