Demonstration of a high sensitivity GNSS software receiver for indoor positioning

Advances in signal processing techniques contributed to the significant improvements of GNSS receiver performance in dense multipath environments and created the opportunities for a new category of high-sensitivity GNSS (HS-GNSS) receivers that can provide GNSS location services in indoor environments. The difficulties in improving the availability, reliability, and accuracy of these indoor capable GNSS receivers exceed those of the receivers designed for the most hostile urban canyon environments. The authors of this paper identified the vector tracking schemes, signal propagation statistics, and parallel processing techniques that are critical to a robust HS-GNSS receiver for indoor environments and successfully incorporated them into a fully functional high-sensitivity software receiver. A flexible vector-based receiver architecture is introduced to combine these key indoor signal processing technologies into GSNRx-hs™ – the high sensitivity software navigation receiver developed at the University of Calgary. The resulting receiver can perform multi-mode vector tracking in indoor environment at various levels of location and timing uncertainties. In addition to the obvious improvements in time-to-first-fix (TTFF) and signal sensitivity, the field test results in indoor environments surrounded by wood, glass, and concrete showed that the new techniques effectively improved the performance of indoor GNSS positioning. With fine GNSS timing, the proposed receiver can consistently deliver indoor navigation solution with the horizontal accuracy of 2–15 m depending on the satellite geometry and the indoor environments. If only the coarse GNSS timing is available, the horizontal accuracy of the indoor navigation solution from the proposed receiver is around 30 m depending on the coarse timing accuracy, the satellite geometry, and the indoor environments. From the preliminary field test results, it has been observed that the signal processing sensitivity is the dominant factor on the availability of the indoor navigation solution, while the GNSS timing accuracy is the dominant factor on the accuracy of the indoor navigation solution.     

过失速飞机最速指向目标机动研究

基于飞机质点动力学模型建立了指向活动目标的终端条件,并进行最速指向机动动作的数值优化,其中用共轭梯度法寻优,用罚函数处理约束条件.计算结果表明,优化可以指导寻找对应于不同战术要求的有利机动过程;在近距空战中,具有快速改变航迹方向并进入过失速超大迎角机动的能力非常有利于快速指向目标、争取首攻机会,而改变航迹方向倾向于使用最大升力区迎角.     

自组织时分多址甚高频数据链的延时分析

时隙预约方法对自组织时分多址系统的延时性能有很大影响.针对动态时隙分配方案中典型的回溯搜索算法,分析了时隙空闲概率及预约冲突概率对报文延时的影响,并采用概率周期分析方法,通过引入时隙处于空闲和忙状态的概率,详细分析了报文延时与用户数和发报率的关系.最后,提出了一种新的时隙选择算法——序贯搜索算法.仿真结果表明,该算法的延时性能比回溯搜索算法优越.      

IEEE 1394协议虚拟复合MAC工业现场总线研究

为解决一个总线回路中不同类型设备通信的性能和效率问题,提出一种采用IEEE 1394总线协议和虚拟复合MAC(Media Access Control)的工业现场总线协议.在IEEE 1394基本协议层的基础上设计虚拟MAC子层,通过附加总线配置实现节点功能的区分,利用等时数据传输和异步数据传输实现时分多址、仲裁、轮询、令牌等MAC方式的数据通信.      

无人机复杂环境中跟踪运动目标的实时航路规划

在复杂地形环境中,无人机在跟踪运动目标时,现有的航路规划方法在实时性和可行性上存在一定缺陷.提出了一种新的滚动窗口启发方向计算方法,使其能够跟踪运动目标,同时在滚动窗口内采用流函数法进行避障.根据无人机约束,滚动窗口为三角形,并设计了基于行为的伸缩功能.在流函数中,利用水势能方法克服了陷阱地形并进行了航路平滑.仿真结果表明:这种混合算法对于复杂地形条件下跟踪运动目标的航路规划,能够减小规划算法的时间和空间复杂度,使规划出的航路适于无人机飞行.     

集成式随动装置目标引导信息动态校准方法研究

光电对抗系统在机动状态下搜索和跟踪目标时,必须用位置陀螺代替码盘来确定目标方位角。但是,由于搜索轴陀螺存在漂移和累积误差,导致跟踪转台按照引导信息调转到位后目标无法进入跟踪视场,而且陀螺的漂移和累积误差是随时间和温度非线性变化的,很难直接进行修正。为了解决这个问题,提出了一种对引导信息进行间接动态校准的方法。     

交互式多模型粒子滤波优化重采样算法

针对标准交互式多模型粒子滤波(IMMPF)算法中存在粒子退化及多样性匮乏问题,提出了交互式多模型粒子滤波优化重采样(IMMPFOR)算法,利用线性优化理论改善模型中具有小权值的粒子精度。该算法的新颖性体现在给定量测信息条件下,利用线性优化方法及模型交互概率将每个模型中拥有小权值的粒子替换成新的粒子。新的粒子既包含本模型中粒子信息,又包含了本模型与其他模型交互后的粒子信息。目标跟踪的仿真结果证明:每个模型新产生的粒子集合可以准确地近似真实状态后验概率密度函数,系统的估计精度与标准IMMPF算法相比有较大提升。     

基于变迹滤波的MIMO-SAR图像分辨率增强技术

针对多输入多输出合成孔径雷达(MIMO-SAR)在近场目标散射特征诊断成像中,非正交旁瓣难以通过常规方法进行有效抑制的问题,分析了MIMO-SAR图像非正交旁瓣的产生机理,提出了基于空间变迹滤波(SVA)和三变迹处理相结合的旁瓣抑制方法。仿真和实验结果表明,本文方法不仅能很好地抑制距离向旁瓣,而且对于方位向非正交旁瓣也具有较好的抑制效果,提高了MIMO-SAR图像的二维分辨率和动态范围。