后验Monte Carlo-Gaussian采样粒子滤波WSN网络定位*

环境因素导致无线传感器网络定位存在噪声影响,实质上是非平滑的非线性问题,针对传统粒子滤波算法在处理该问题时精度不高的缺点,提出一种基于后验泊松分布的Monte Carlo-Gaussian重采样粒子滤波算法的无线传感器网络定位算法。首先,基于粒子滤波算法,借鉴扩展卡尔曼滤波算法采用近似后验高斯分布思想,设计了后验泊松分布Monte Carlo-Gaussian重采样粒子滤波器。其次,采用该滤波器设计实现了无线传感器网络定位算法,解决了非平滑非线性的噪声干扰定位问题。最后,分别对滤波器和定位算法的性能进行了对比仿真实验,结果验证了所提算法的有效性。     

融合深度与肤色特征的自适应手部跟踪算法

手部跟踪技术是实现自然人机交互的关键。针对现有跟踪方法易受光照、环境等影响及鲁棒性差的不足,提出一种融合深度与肤色特征的自适应手部跟踪算法。考虑手部运动过程的形变,该算法首先利用深度平滑连续性选取深度阈值以实现跟踪区域的自适应尺度变化,获得手部候选区域。在此基础上建立YCbCr空间肤色归一化直方图,在粒子滤波框架下将跟踪问题转换为贝叶斯估计问题,基于最大后验准则确定手部位置,并通过监测粒子重要性权值的方差解决跟踪失效问题,实现复杂观测环境下的鲁棒跟踪。实验结果表明,该跟踪算法可适应不同复杂环境,鲁棒性良好。     

Design and experimental evaluation of robust controllers for a two-wheeled robot

The paper presents the design and experimental evaluation of two alternative μ-controllers for robust vertical stabilisation of a two-wheeled self-balancing robot. The controllers design is based on models derived by identification from closed-loop experimental data. In the first design, a signal-based uncertainty representation obtained directly from the identification procedure is used, which leads to a controller of order 29. In the second design the signal uncertainty is approximated by an input multiplicative uncertainty, which leads to a controller of order 50, subsequently reduced to 30. The performance of the two μ-controllers is compared with the performance of a conventional linear quadratic controller with 17th-order Kalman filter. A proportional-integral controller of the rotational motion around the vertical axis is implemented as well. The control code is generated using Simulink® controller models and is embedded in a digital signal processor. Results from the simulation of the closed-loop system as well as experimental results obtained during the real-time implementation of the designed controllers are given. The theoretical investigation and experimental results confirm that the closed-loop system achieves robust performance in respect to the uncertainties related to the identified robot model.     

Simultaneous state estimation and parameter identification in linear fractional order systems using coloured measurement noise

In the present paper, the identification and estimation problem of a single-input–single-output (SISO) fractional order state-space system will be addressed. A SISO state-space model is considered in which parameters and also state variables should be estimated. The canonical fractional order state-space system will be transformed into a regression equation by using a linear transformation and a shift operator that are appropriate for identification. The identification method provided in this paper is based on a recursive identification algorithm that has the capability of identifying the parameters of fractional order state-space system recursively. Another subject that will be addressed in this paper is a novel fractional order Kalman filter suitable for the systems with coloured measurement noise. The promising performance of the proposed methods is verified using two stable fractional order systems.     

A skewed unscented Kalman filter

State estimation of nonlinear systems is a challenging task, especially when the Gaussian approximation fails. The unscented Kalman filter was proposed to deal with state estimation of nonlinear systems. We modify the traditional unscented Kalman filter to capture the third-order moment (skewness) of the state vector. Methods are also proposed to reduce the computation time of the suggested approach, and showing that the proposed algorithm is as fast as the unscented Kalman filter. Simulation results confirm that the method is better than, or at least as good as, the unscented Kalman filter.     

基于雾气浓度估计的图像去雾算法

根据雾气浓度的视觉特征,提出一种雾气浓度估计模型.在此基础上,结合大气散射模型,提出一种新的图像去雾算法.首先,基于雾气浓度估计模型计算出雾气浓度量化图,利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光; 然后,对量化图中的“非雾气最浓”区域再次进行聚类处理,根据文中所提最优透射率评价指标估计出每个聚类单元的透射率,将全球光与透射图以及有雾图像导入散射模型,便可达到去雾的目的; 最后,针对去雾后图像较实际场景偏暗,提出一种基于小波域的多尺度锐化算法进行增强处理,以改善其主观视觉质量.实验结果表明,本文算法与现有主流算法相比,具有更好的去雾效果,并且其计算速度也相对较快.     

萤火虫算法智能优化粒子滤波

针对粒子滤波(Particle filter, PF)重采样导致的粒子贫化以及需要大量粒子才能进行状态估计的问题,本文结合粒子滤波的运行机制,对萤火虫算法的寻优方式进行修正,设计了新的萤火虫位置更新公式和荧光亮度计算公式,并在此基础上提出了萤火虫算法智能优化粒子滤波.该方法引入了萤火虫群体的优胜劣汰机制以及萤火虫个体的吸引和移动的行为,使粒子群智能地向高似然区域移动,提高了粒子群的整体质量.实验表明该方法提高了粒子滤波的预测精度,同时大大降低了状态值预测所需的粒子数量.     

Nonlinear aircraft sensor fault reconstruction in the presence of disturbances validated by real flight data

This paper proposes an approach for Inertial Measurement Unit sensor fault reconstruction by exploiting a ground speed-based kinematic model of the aircraft flying in a rotating earth reference system. Two strategies for the validation of sensor fault reconstruction are presented: closed-loop validation and open-loop validation. Both strategies use the same kinematic model and a newly-developed Adaptive Two-Stage Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodeled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.     

采用双状态传播卡方检验和模糊自适应滤波的容错组合导航算法

太阳能高空长航时无人机导航系统中,捷联惯导/北斗2κ全球卫星导航/星光导航(SINS/BD2/GPS/CNS)是一种可用的组合方案.针对常规容错组合导航算法故障检测类型单一,故障时滤波精度下降的问题,提出一种采用双状态卡方检验(TSPCST)和模糊自适应滤波(FAF)的容错组合导航算法.为了同时检测多种故障,将TSPCST应用于联邦滤波结构中;为了防止故障数据污染系统,利用FAF输出的高精度导航信息,对双状态传播器定期交替校正;进一步,FAF运用TSPCST检测得到的故障信息变量,定义量测子系统模糊有效域,将检测阈值模糊化,以弥补常规固定检测阈值算法难以选取阈值的不足;最后,通过计算信息分配因子,自适应处理多种故障数据.仿真结果表明,该容错组合导航算法性能优于常规固定检测阈值算法.     

中医针灸领域术语自动抽取研究

针对中医针灸领域术语的构成特点,该文建立了一种基于规则的领域术语抽取算法模型,该模型首先对中医针灸领域术语种子集进行有限次的迭代,生成中医针灸领域术语构件集;然后,以术语构件集为领域词典,采用最大向前匹配算法对中文针灸医学文献中的句子进行切分,并抽取候选术语;最后,利用语言规则对候选术语进行过滤处理,筛选出中医针灸领域专业术语。分别以关键字集和中医词典为种子集进行实验,开式测试的F值分别达到76.96%和35.59%。