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.     

利用CFD技术计算飞行器动导数

利用非定常流场数值计算方法模拟飞行器强迫俯仰振荡仅能得到俯仰力矩系数对迎角变化率和俯仰角速度的动导数之和,而动稳定性分析需要单独的动导数数值.为解决这个问题,利用滑移网格模拟强迫振荡运动,得到俯仰力矩系数对迎角变化率和俯仰角速度的动导数之和.利用旋转参考坐标系模拟定常拉升,得到俯仰力矩系数对俯仰角速度的动导数.利用旋转参考坐标系模拟匀速滚转,得到滚转力矩系数对滚转角速度的动导数.对有翼导弹和水上飞机进行了纵向和横向动导数的计算.计算结果与试验数据、文献数据以及其他方法得到的结果具有较好的一致性,表明提出的方法可用于复杂外形飞行器动导数计算.     

国外高超声速组合推进技术概述

推进技术是高超声速武器的核心技术,以超燃冲压发动机为基础的高超声速组合推进技术是高超声速武器的首选动力方案。本文介绍了几种以超燃冲压发动机为基础的组合推进方案,并简要介绍了美国、日本以及印度的技术发展现状。     

高速气流场燃油雾化液滴分布数值研究

针对亚燃冲压发动机燃烧室内部流动特点,结合二元稳定器试验台高速气流场燃油雾化特性试验,建立试验件三维模型并对其喷雾两相流动进行数值模拟。主要研究了来流马赫数以及喷嘴条件变化时燃油雾化液滴与油气比的分布。分析认为,来流马赫数的增加使得雾化特征角缩小,可同时改善燃油蒸发并获得更加均匀的油气比分布。随着供油压力的提高,离心式与直流式喷嘴雾化特征角均增大,但供油压力不是影响直流喷嘴雾化锥角的主要因素。计算结果与试验结果对比定性符合良好,定量误差范围可以接受,验证了计算模型与计算方法的正确性,所得到的结果可应用于工程设计。     

推进剂供应系统增压过程仿真

在大型液体火箭推进系统中,推进剂供应系统对贮箱压力有着严格的要求,增压系统作为可靠性环节的关键系统,工作过程复杂,需要进行仿真分析和试验验证,以改进设计。应用系统仿真技术,对某推进剂供应系统的增压过程进行了仿真,仿真结果与试验情况基本吻合。仿真结果表明缓冲阀可以有效地抑制增压过程压力振荡。此外,系统增压时间不能低于17s。     

我国载人登月重型运载火箭动力系统探讨

月球研究与利用是21世纪航天发展的重点之一。根据载人登月的需求,探讨了我国重型运载火箭及其动力系统的技术途径,提出研制大推力液氧/烃和液氧/液氢发动机的设想。重点论证了大推力下面级发动机的推进剂组合、动力循环方式及推力量级,认为该发动机推进剂应选择环保、廉价及高性能的液氧/烃组合,动力循环方式应采用先进的补燃循环或低成本的燃气发生器循环,推力应为4000kN左右。     

易于硬件实现的遥感图像两倍压缩算法

结合干涉多光谱遥感图像航天应用的要求,参考CCSDS标准无损压缩算法,提出了一种易于硬件实现的干涉多光谱遥感图像无损／近无损压缩算法。该算法在对12bit干涉多光谱图像进行2倍压缩时压缩性能与JPEG 2000标准算法相当,但算法复杂度和所需存储空间大大降低,在单片FPGA内部即可实现全部压缩功能,可以很好地满足航天应用的要求。     

航天器热平衡试验中的热流测量技术

文章介绍了在航天器热平衡试验中到达航天器表面或被其吸收的红外辐射热流密度的测量技术。     

质心位置对超空泡射弹尾拍运动影响分析

基于均质平衡流理论,通过求解混合介质的RANS(Reynolds-Averaged Navier-Stokes equations)方程、SST(Shear Stress Transport)湍流方程和不同介质之间的质量输运方程,结合刚体运动方程和网格变形方法,研究了不同质心位置的超空泡射弹尾拍运动特性以及尾拍运动下超空泡形态特性,对比分析了不同质心位置的超空泡射弹尾拍运动的刚体运动和尾拍力的变化特征.结果表明,射弹尾拍运动对空泡形态的对称性有较大影响,发生碰撞处的空泡壁面朝着弹体转动的方向发展;射弹尾拍运动的转动角度、角速度、角加速度以及尾拍阻力和尾拍升力等都表现出周期性变化规律,且随着质心与射弹头部距离的增加,转动惯量增大,变化周期也增大.     

A Gaussian Mixture PHD Filter for Jump Markov System Models

The probability hypothesis density (PHD) filter is an attractive approach to tracking an unknown and time-varying number of targets in the presence of data association uncertainty, clutter, noise, and detection uncertainty. The PHD filter admits a closed-form solution for a linear Gaussian multi-target model. However, this model is not general enough to accommodate maneuvering targets that switch between several models. In this paper, we generalize the notion of linear jump Markov systems to the multiple target case to accommodate births, deaths, and switching dynamics. We then derive a closed-form solution to the PHD recursion for the proposed linear Gaussian jump Markov multi-target model. Based on this an efficient method for tracking multiple maneuvering targets that switch between a set of linear Gaussian models is developed. An analytic implementation of the PHD filter using statistical linear regression technique is also proposed for targets that switch between a set of nonlinear models. We demonstrate through simulations that the proposed PHD filters are effective in tracking multiple maneuvering targets.