基于权值分配及多特征表示的在线多示例学习跟踪

针对复杂环境下目标跟踪过程中由于遮挡、目标姿势及光照条件变化引起跟踪漂移的问题,提出一种基于多示例学习（MIL）框架的在线视觉目标跟踪算法。该算法针对多示例跟踪算法采用单一haar-like特征不能准确描述目标外观变化及在学习过程中对样本包中各正负样本示例采用相同权值,忽略不同正负样本示例在学习过程中对包的重要性不同的特点,采用多特征联合表示目标外观构造分类器,通过将多特征互补特性融入在线多示例学习过程中,利用多特征的互补属性建立准确的目标外观模型,克服在线多示例跟踪算法对目标外观变化描述不足的问题;同时,依据不同正负样本示例对样本包的重要程度进行权值分配,提高跟踪精度。实验结果表明,本文跟踪算法对场景光线剧烈变化、遮挡、尺度变化及平面旋转等干扰具有较强的跟踪鲁棒性,通过对不同视频序列进行测试,文中算法在5组测试视频序列上的平均中心位置误差远小于对比增量式学习跟踪,仅为10.14像素,其对比算法IVT、MIL和OAB的中心位置误差分别为17.99、20.29和33.64像素。      

Particle flters for probability hypothesis density flter with the presence of unknown measurement noise covariance

In Bayesian multi-target fltering,knowledge of measurement noise variance is very important.Signifcant mismatches in noise parameters will result in biased estimates.In this paper,a new particle flter for a probability hypothesis density（PHD）flter handling unknown measurement noise variances is proposed.The approach is based on marginalizing the unknown parameters out of the posterior distribution by using variational Bayesian（VB）methods.Moreover,the sequential Monte Carlo method is used to approximate the posterior intensity considering non-linear and non-Gaussian conditions.Unlike other particle flters for this challenging class of PHD flters,the proposed method can adaptively learn the unknown and time-varying noise variances while fltering.Simulation results show that the proposed method improves estimation accuracy in terms of both the number of targets and their states.     

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.     

基于鲁棒自适应反步法的航天器姿态跟踪控制

针对存在未知惯量矩阵和外干扰的刚体航天器姿态跟踪,提出了一种鲁棒自适应控制方法。综合自适应反步法和非线性L2增益干扰抑制方法,用自适应反步法构造系统的Lyapunov函数,获得了具L2增益的鲁棒自适应控制器,以保证姿态跟踪误差系统为一致最终有界稳定,确保估计的航天器惯量参数的有界性,并使从外干扰输入到评价输出的L2增益不大于给定值。仿真结果验证了方法的有效性和可行性。     

GNSS接收机数字载波跟踪环建模与噪声性能分析

针对GNSS接收机高灵敏度跟踪问题,研究数字载波跟踪环热噪声相位颤动与相干积累时间长度的关系.在分析I·Q鉴相器的Costas载波环信号处理流程的基础上,建立了新的环路线性化模型.基于该模型,推导了由最佳模拟环路滤波器双线性变换离散化得到的数字载波跟踪环的噪声性能.数值分析表明:采用I·Q鉴相器的二阶、三阶数字载波环热噪声相位颤动,随相干积累时间的增大先减小后增大,存在热噪声相位颤动最小意义上的最佳相干积累时间.仿真结果验证了理论分析结论,同时表明新建模型对数字载波跟踪环的描述比传统模型更准确.文中给出的各载噪比和环路带宽组合条件下的最佳相干积累时间,可用于指导高灵敏度接收机载波跟踪环设计.     

运载器末助推段非线性姿态控制器设计

根据单摆模型近似晃动质量推导晃动运动与姿态运动的动力学方程,基于状态相关黎卡提方程方法,综合动态逆控制方法设计了运载器末助推段非线性姿态控制器,由状态反馈实现姿态跟踪和晃动抑制。因实际中模拟晃动运动的单摆状态无法测量,引入输出多采样率技术,通过在一个采样周期内多次检测被控对象的输出估计状态,实现设计的状态反馈控制律。数...     

单周期冲跃飞行轨迹性能参数影响程度分析

对高超声速飞行器的单周期冲跃飞行轨迹进行了研究。建立了动力学模型和约束条件。仿真分析了升阻比、初始速度和初始弹道倾角对飞行轨迹性能的影响,并讨论了影响程度,确定了适于该飞行器的最佳飞行走廊,为后续的冲跃飞行轨迹完整设计和优化提供了参考。     

基于梯度方向二值模式特征的飞机翼尖跟踪技术

研究基于视频图像分析与定位的飞机翼尖跟踪技术,为飞机地面移动提供安全保障.现有图像特征进行翼尖跟踪经常失效且计算效率低下,本文结合纹理和轮廓信息,提出以梯度方向二值模式( OG_ LBP)为特征的粒子滤波跟踪算法,降低特征维数的同时建立局部和全局的翼尖特征直方图描述,提高识别效果.同时,该算法在粒子滤波基本框架之下,结...     

DLR-F6翼身组合体数值计算

使用自行研制的混合网格亚跨超声速流场解算器程序MFlow计算了AIAA第三届阻力会议提供的DLR-F6及其带整流装置FX2B情况下的阻力。重点分析了两者的网格收敛特性、阻力极曲线以及压力分布等,并与阻力会议的各个软件的计算结果进行比较。详细分析了DLR-F6翼身结合处后缘附近网格精度对分离气泡计算的影响。计算结果表明,MFlow程序的计算精度与国外软件相近,能够为阻力计算提供比较精确的结果。     

基于阻力分解策略的翼型阻力计算方法研究

研究并应用了基于翼型阻力分解策略的中场积分计算阻力的方法。中场积分方法是近年来提出的一种新的计算阻力的方法,方法将流场分为三个不同的区域：波阻区、型阻区、数值耗散区,通过对不同区域进行积分将阻力分解为波阻、型阻、数值耗散阻力。计算结果表明中场积分方法与传统的表面积分方法和远场积分方法相比,不仅可以将阻力分解成不同部分以便于进一步分析阻力产生机理,而且在计算中对网格量的要求较低,即使在网格量较小的情况下也能得到较精确的结果。