Sage-Husa自适应滤波在运动障碍物轨迹预测中的应用

针对机器人在复杂的工作环境下安全避开运动障碍物与传感器感知信息中存在噪声的问题,提出基于Sage-Husa自适应滤波方法对障碍物的运动轨迹进行预测.该算法以卡尔曼滤波为主体,同时融入具有时变性能的噪声估计器.使得在轨迹预测过程中,能够预估和更新噪声的实时变化.对Sage-Husa自适应滤波相比卡尔曼滤波的改进进行探讨,...     

一种新的自适应滤波算法

为了解决SVS_LMS算法中步长更新函数较为复杂的问题,提出一种改进的LMS自适应滤波算法。新的算法利用瞬时误差的幂函数对步长更新进行控制,同时根据MVSS_LMS算法中误差自相关估计补偿原理,采用当前步长因子和上一时刻步长的相关估计对步长因子进行补偿。通过仿真比较,新的算法相较于SVS_LMS和MVSS_LMS的改进算法具有更快的收敛速度及更小的稳态失调误差。     

基于信息质量的脉冲星导航自适应滤波算法

针对脉冲星导航过程中观测脉冲星的可见性问题,提出了一种基于信息质量的自适应滤波算法。通过分析观测脉冲星的数目及信息质量,确定观测矩阵维数,实时生成观测矩阵,设计了适应观测信息变化的改进型Kalman滤波器。对观测信息质量重新做了定义,并据此构造滤波方程提高了脉冲星导航的精度及适应性;运用四阶龙格库塔方法对带有J2摄动的二体动力学方程进行线性离散化,提高了滤波器状态方程的线性离散化精度。进行了仿真实验,对改进型Kalman滤波算法进行了验证。结果显示,对初始偏差校正后,在10 000s内观测一颗或两颗脉冲星,导航位置精度可达40m,速度精度可达0.019m/s。得到的结果验证了提出算法的有效性和可行性。     

自适应滤波协同图优化导航方法研究

针对传统图优化导航方法中传感器测量协方差不准确导致估计精度下降的问题,本文提出了一种自适应滤波协同图优化导航方法。首先,构建INS/GNSS/e-Compass组合导航系统的因子图模型;然后,利用测量方差自适应滤波对传感器测量信息进行预估,在滤波过程中更新相关传感器的测量协方差矩阵,并将预估结果作为变量节点加入因子图;最后,通过滑动窗口控制优化范围,对窗口内的变量节点进行非线性优化并输出最终的导航状态。仿真和实验结果表明,所提出的方法对传感器测量协方差的不匹配问题具有自适应性,能够在不同场景下实现高效可靠的导航定位。相比于传统图优化方法,该方法的定位精度提升了30%,计算效率提升了12%。     

基于改进联邦滤波算法的组合导航系统的应用

针对组合导航系统中联邦滤波信息融合算法在滤波精度和容错性能等方面存在的不足,提出了一种基于以捷联惯导系统(SINS)为公共主系统,全球定位系统(GPS)和多普勒测速系统(DVL)为辅助子系统的改进联邦滤波算法的组合导航系统。介绍了卡尔曼滤波原理与信息融合算法的特点,基于联邦滤波器的组合形式详细阐述了联邦滤波器设计步骤,将改进量测噪声协方差阵的自适应联邦滤波器应用到SINS/GPS/DVL组合导航系统中,并对此系统进行了MATLAB仿真。仿真结果表明,相较于标准联邦滤波器算法,该文设计的基于改进量测噪声协方差阵的自适应联邦滤波器能明显提高组合导航系统的滤波精度和可靠性。     

一种新的变步长LMS自适应滤波算法性能分析

在简单介绍了基本的LMS,NLMS自适应滤波算法的基础上,介绍了一种新的可变步长LMS自适应滤波算法,并将该算法应用于自适应噪声对消系统的仿真中.通过计算机仿真,给出了LMS、NLMS和新的可变步长LMS自适应滤波三种算法的性能对比,结果表明该算法具有较快的收敛速度和较小的稳态误差.     

工程扫描图的一种新型的自适应中值滤波算法

工程扫描图平滑处理常采用的中值滤波器能够有效去除噪声，但也会引起图像中诸如细线、角点等重要细节信息的丢失和破坏。提出基于多个子窗口的自适应的中值滤波算法，在处理每一个像素时，把多个方向的子窗口同时作用于该像素，比较这些子窗口的灰度一致性，然后选择灰度一致性较高的子窗口的中值，作为处理后的该像素的灰度值。以一种标准测试图像和实际扫描图为例，对标准中值滤波器和所提出的算法进行了对比试验，结果表明后者具有较好的细节保护能力和较强的滤噪特性。     

一种基于噪声连接分量的自适应层次中值滤波算法

针对椒盐噪声污染图像的降噪,提出一种基于噪声连接分量的自适应层次中值滤波算法。首先根据椒盐噪声像素点的邻接关系和分布特点,对噪声定位图像实施标记处理;然后计算各连接分量集合中元素的个数,将噪声定位图像分层,得到层次噪声定位图像;最后按照由低层到高层的顺序,逐层对噪声污染图像进行标准中值滤波处理,而标准中值滤波的窗口大小则依据连接分量自适应地进行调整,最终得到滤波结果。将该算法与标准中值滤波、自适应中值滤波进行仿真实验,并与其他中值滤波算法就指标PSNR进行比较,均表明该算法降噪效果优良。     

基于低成本多传感器的自适应组合滤波

研究了基于硅微机电系统(MEMS)陀螺、加速度计及磁阻式磁强计组合的微小型飞行器用姿态航向参考系统.针对传统航姿算法无法保证微小型飞行器在长时间、高机动情况下以较高精度保持姿态航向的问题,提出了一种基于低成本多传感器的自适应组合滤波算法.该算法首先通过对运动加速度和磁干扰进行建模并将其引入状态方程来保证载体在长时间高机...     

一种应用于LED封装机对准系统的参数自适应滤波算法

高性能的LED封装机对准系统需要能够准确地对图像中的标记的边缘进行定位,而一般的图像平滑滤波算法对标记的边缘也会起到平滑作用,导致边缘定位不准确。针对这个问题,提出了一种根据经典Lee滤波算法改进的滤波算法,对Lee滤波算法的关键参数的计算公式进行了改进,利用三角函数和局部灰度值统计信息来表示其取值式,使得其可以利用图像的局部灰度数学统计程序化地计算出算法参数的适宜取值,从而使算法脱离了人工的干预。实验证明,改进后的Lee滤波算法能够在无需人工给定参数的情况下,快速完成参数的自适应选取,从而实现对同一图像的不同部分各采用不同的、合理的滤波系数,实现滤波。     

Experiments of optimal delay extraction algorithm using adaptive time-delay filter for improved vibration suppression

In the previously introduced direct adaptive command shaping filter (ACSF), the time-delay value is fixed and only the magnitudes of the impulses are learned. The performance of the direct adaptive time-delay command shaping filter, however, depends on the select time-delay. In this paper, the authors introduce a new scheme to extract the optimal time-delay value for the improved vibration suppression in flexible motion system. To develop the optimal time-delay extraction scheme, the authors have analyzed the effect of the time-delay value on the performance of the direct ACSF. Based on the analysis result the authors have established a set of equations to extract the optimal time-delay toward the optimal vibration suppression performance of ACSF. Experimental results using a gantry robot with a single flexible link show the effectiveness of the proposed time-delay adaptation approach for the improved vibration suppression. This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008. Joo Han Park received the B.S. and M.S. degrees in Mechanical Engineering from the Kyung Hee University, Korea, in 2005 and 2007. He is currently a candidate for the PhD at Kyung Hee University, Korea. His research interests include robotics and vibration control. Sungsoo Rhim received his B.S. and M.S. degrees in Mechanical Engineering from Seoul National Univ., Korea, in 1990 and 1992 respectively. He then received his Ph.D. degree from Georgia Institute of Technology in 2000. He worked for CAMotion, Inc. in GA, USA, as Research Director from 2000 until 2003 and he is currently an Assistant Professor at the Dept. of Mechanical Engineering in Kyung Hee Univ., Korea. His research interests include system dynamics, control, robotics and vibration.     

基于运动目标自适应检测的改进ViBe算法

传统视觉背景提取(ViBe)算法检测结果存在Ghost区域,且受环境变化影响,在提取前景时容易产生误检或漏检。针对这些问题,提出了一种基于运动目标自适应检测的改进ViBe算法。首先在背景模型初始化过程中,通过对均值背景建模设置调节参数方式获取真实背景,利用该背景初始化ViBe背景模型;其次在前景检测过程中,根据场景变化引入自适应半径阈值对前景进行自适应检测;最后对检测结果中存在的空洞进行数学形态学闭运算填充。实验结果表明,改进算法能够有效抑制Ghost区域,并在环境变化的情况下较完整地检测前景目标,与传统ViBe算法相比,检测的精确率提高了10%以上,误检率和漏检率分别降低了20%和7%,且改进算法满足实时性要求。     

An Improved Cooperative Adaptive Cruise Control （CACC） Algorithm Considering Invalid Communication

For the Cooperative Adaptive Cruise Control （CACC） Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.     

移动机器人自适应抗差无迹粒子滤波定位算法

针对机器人定位过程中传感器感知信息存在野值,加剧粒子退化,导致机器人状态参数滤波值失真,甚至出现定位失败的问题,提出一种机器人自适应抗差无迹粒子滤波定位算法。在重要性采样阶段利用无迹卡尔曼滤波产生优选的建议分布函数,降低系统估计误差,同时有效提升系统的抗噪声能力。同时利用抗差估计原理构造抗差方差分量统计量,并由该统计量引入的自适应因子调节增益矩阵,减弱野值对滤波的影响。实验结果表明,当观测数据中存在野值时,该算法能够有效地控制观测异常误差的影响,定位精度得到了很大提高,并在不同系统噪声和观测噪声方差下,具有较强的鲁棒性和实时性。     

自适应空间载波相移算法

介绍了一种自适应空间载波相移算法。模拟和实验结果显示该算法能测量位相分布变化较剧烈的三维物面而勿须知道条纹载波频率;其模拟测量精度在无噪声情况下达到1-0 3rad。     

An improved simplex-based adaptive evolutionary digital filter and its application for fault detection of rolling element bearings

The de-noising performance and convergence behavior of the adaptive evolutionary digital filter (EDF) are restricted by the factors of constant evolutionary coefficients and taking the reciprocal of average energy of residual signal as the fitness function. In this paper, an improved adaptive evolutionary digital filter based on the simplex method (EDF-SM) is proposed to overcome the shortcomings of the original EDF. A new evolutionary rule was constructed by introducing the simplex-based mutating method and by then combining this with the original cloning and mating methods. The reciprocal of sample entropy was taken as the fitness function and variable evolutionary coefficients were employed. Numerical examples show that the proposed EDF-SM exhibits a higher convergence rate and a better de-noising behavior than the other EDFs. The effectiveness of the proposed method in discovering fault characteristics and detecting faults of rolling element bearings is supported using an experimental test.     

Time-optimal trajectory planning based on improved adaptive genetic algorithm

This paper investigates a trajectory planning algorithm to reduce the manipulator's working time.A time-optimal trajectory planning (TOTP) is conducted based on improved adaptive genetic algorithm (IAG...     

基于限制自适应卡尔曼滤波器的连续旋转寻北算法研究

寻北仪作为方位测量装置,被广泛应用在军事和民用定向和控制领域。针对传统寻北仪方法存在的缺陷,提出了基于测量地球自转角速度分量的连续旋转调制动态寻北方案。通过动态误差建模、优化过程约束和动态噪声估计,设计了延时补偿和硬件修正方案及限制自适应卡尔曼滤波算法。经仿真及试验验证,该算法鲁棒性好,抗噪声能力强,寻北精确度高。     

改进自适应噪声对消算法的窄带干扰抑制

在局部放电在线检测中,自适应噪声对消算法是当前抑制窄带干扰的有效方法.由于窄带干扰频率范围很宽,滤波参数不易设置,同时实测时的窄带干扰在时频域都表现强烈,局部放电信号会完全淹没于干扰之中,使得一般改进噪声对消算法不能取得较好效果.为此,提出一种改进经验模态分解的噪声对消算法,首先在频域中降低干扰幅值,接着利用经验模态分解的分频特性将宽频带的窄带干扰分解到不同频带,各频带内的窄带干扰频率相差有限,然后进行自适应噪声对消,以达到较好的滤波性能.仿真和实际数据验证了该算法的有效性.