简化UKF算法在SINS／GPS组合导航中的应用

针对SINS／GPS组合导航系统的特点,建立了系统的非线性误差模型。根据系统状态方程为非线性而观测方程为线性的特点,将一种简化的UKF方法（Rao-Blackwellisation Additive Unscented Kalman Filter,RBAUKF）用于SINS／GPS组合导航系统中,RBAUKF采用较少的采样点数目和简化的更新算法,降低了计算复杂度。最后,在机动条件下,进行了SINS／GPS组合导航实验仿真。仿真结果表明,RBAUKF相比EKF具有更高的滤波精度,更适合在SINS／GPS组合导航系统中应用。     

Effective assessment of tyre–road friction coefficient using a hybrid estimator

Vehicle stability and active safety control depend heavily on tyre forces available on each wheel of a vehicle. Since tyre forces are strongly affected by the tyre–road friction coefficient, it is crucial to optimise the use of the adhesion limits of the tyres. This study presents a hybrid method to identify the road friction limitation; it contributes significantly to active vehicle safety. A hybrid estimator is developed based on the three degrees-of-freedom vehicle model, which considers longitudinal, lateral and yaw motions. The proposed hybrid estimator includes two sub-estimators: one is the vehicle state information estimator using the unscented Kalman filter and another is the integrated road friction estimator. By connecting two sub-estimators simultaneously, the proposed algorithm can effectively estimate the road friction coefficient. The performance of the proposed estimation algorithm is validated in CarSim/Matlab co-simulation environment under three different road conditions (high-μ, low-μ and mixed-μ). Simulation results show that the proposed estimator can assess vehicle states and road friction coefficient with good accuracy.     

基于UKF滤波的SAS水下导航方法

合成孔声呐（SAS）运动补偿的一种重要方法是利用导航设备记录声纳载体各时刻的运动状态来修正回波数据以达到成像运动补偿的目的．研究和利用高精度的组合导航方法进行合成孔径声呐的水下运动估计是其中的关键技术之一．文中研究了基于光纤陀螺罗经Octans和多普勒声速剖面仪ADCP的SAS水下导航方法,并利用UKF滤波技术进行SAS的运动参数估计,仿真结果取得了较好的估计精度．     

基于UKF算法的车辆质心侧偏角估计

将无味卡尔曼滤波(UKF)算法运用到车辆质心侧偏角的估计之中,基于纵滑—侧偏联合工况下的统一指数(Uni-tire)轮胎模型建立非线性车辆动力学模型,采用最小偏度单形采样的UKF算法估计车辆的几个关键状态参量,并由此得到质心侧偏角估计。最后采用奇瑞A3两厢型汽车的车辆参数,使用车辆动力学实时仿真软件DYNAware/veDYNA对观测器进行了实时验证。仿真结果表明,UKF非线性估计方法精度高,估计结果能够满足实际应用要求。     

基于UKF的GPS L1C/A码微弱信号跟踪算法

为了实现高灵敏度的软件接收机,提出了一种基于UKF的GPS L1 C/A码微弱信号跟踪算法.该算法使用UKF实现了微弱信号的L1 C/A码和载波跟踪.通过构建模型,建立方程,并通过采用仿真噪声干扰下的微弱GPS C/A 中频信号对该算法进行实验性能分析.仿真实验结果表明,UKF算法可以实现对载波相位跟踪、载波频率跟踪以及码相位跟踪性能的改善,并且大大简化了计算的复杂度,具有较高的跟踪灵敏度和精度,是一种适合软件接收机实现的算法.     

基于 UKF 非线性人眼跟踪的驾驶员疲劳检测

为解决驾驶员疲劳检测算法中头部快速移动、人眼非线性跟踪以及实际疲劳表情的识别问题,提出了一种新的基于UKF眼跟踪算法的驾驶员疲劳检测方法.根据近似非线性函数的概率分布比近似其函数更容易的原则,利用UT无迹变换,选择一组确定的Sigma点集逼近驾驶员人眼运动状态的后验概率密度函数,进行人眼非线性跟踪.在驾驶员人眼非线性跟踪基础上,通过计算PERCLOS值,进行现实驾驶条件下驾驶员疲劳的跟踪检测.实验结果表明,该方法不仅可以增强对驾驶员头部旋转、快速移动以及光照变换的鲁棒性,而且可以比传统的Kalm an滤波算法提供更精确的计算估计.     

无线传感器网络电子航标节点定位算法研究

介绍了无线传感器网络电子航标节点测距定位的定位原理和算法.针对该定位算法的非线性方程组求解问题,依据UKF算法,用一个最小的样本点集来近似系统状态的分布函数.实现了当系统按实际的非线性模型演化时,对非线性函数的后验均值与方差的很好拟合.仿真结果表明,用UKF算法的节点定位估计精度在5%以内.可见,它在解决非线性机动目标跟踪问题时有比较好的跟踪性能和滤波结果.     

基于固定延迟平滑算法的机动目标跟踪方法

为进一步提高机动目标的跟踪精度和估值算法的数值稳定性,文章基于平方根UKF（square root UKF：SR-UKF）和固定延迟平滑算法（fixed-lag smoothing）提出一种新的固定延迟平方根UKS算法（fixed-lag square root unscentedkal man smoothing：FL-SR-UKS）。数值仿真说明该算法可以有效处理机动目标跟踪问题,且状态估值精度优于SR-UKF。     

基于UKF的Rao-Blackwellized粒子滤波器多传感器多目标跟踪算法研究

在纯方位多传感器多目标跟踪问题中,状态的测量通常是来源未确定的观测量,在杂波环境尤为如此,需要同时解决多个目标的测量和目标之间的关联问题。本文提出一种新的基于Rao-Blackwellized思想的RBPF-UKF算法。该算法利用Rao-Blackwellized将多目标跟踪问题转化为2个子问题:数据关联及单目标跟踪问题,利用粒子滤波中的序列重要性重采样原理解决多目标跟踪的数据关联问题,用UKF滤波器实现单目标跟踪。仿真结果表明,RBPF-UKF算法能很好地解决多目标数据关联问题,与RBPF-EKF算法相比具有更高的滤波精度及稳定性,体现了该算法的优越性。     

State observer-based sliding mode control for semi-active hydro-pneumatic suspension

This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.