基于CKF的SINS大方位失准角初始对准

大方位失准角捷联惯导系统(strapdown inertial narigation system,SINS)误差方程是非线性的,为改善非线性模型下初始对准的精度,提出将一种新的非线性滤波方法(cubature Kalman filter,CKF)应用于捷联惯导系统初始对准中。为此建立了大方位失准角下初始对准非线性模型,分析了基于spherical-radial cubature准则的CKF滤波原理,对非线性模型进行了CKF滤波仿真。仿真结果表明CKF能够很好地处理初始对准中的非线性问题,提高初始对准精度,方位失准角误差能够收敛到-33.13’,接近理论估计精度-32.40’,优于EKF的-84.14’。     

基于CKF的永磁同步电机无传感器控制

永磁同步电机（PMSM）是典型的非线性系统。为提高转速估计精度,提出了将cubatureKalmanfilter（CKF）方法应用在PMSM无速度传感器控制中。和扩展卡尔曼滤波（EKF）算法相比,CKF无需对系统非线性模型进行线性化处理。其根据spherical—radialcubature准则,通过一些相等权值的cubature点经非线性系统方程转换后产生新的点来给出下一时刻系统状态的预测,不需要对系统模型进行线性化处理。文中在对CKF算法分析的基础上,建立了基于CKF的PMSM无速度传感器控制仿真模型,通过和传统的EKF算法的仿真对比实验,验证了CKF算法的有效性和优越性。     

基于高斯混合容积卡尔曼滤波的UUV自主导航定位算法

针对过程噪声为非理想高斯分布时无人水下航行器(UUV)自主导航定位存在噪声模型失配的问题,将高斯混合密度模型与容积卡尔曼滤波(CKF)相结合,设计了基于高斯混合容积卡尔曼滤波(GM-CKF)的UUV导航定位算法。建立了UUV运动模型及观测模型,利用CKF完成各高斯分量的预测更新,并将更新结果进行融合缩减与加权求和,从而实现UUV自主导航定位。通过与EKF、UKF和CKF算法仿真对比实验,验证了GM-CKF可以提高估计精度;通过UUV湖试试验,验证了基于GM-CKF的UUV自主导航定位精度和稳定性优于传统算法,其计算时间满足实时导航定位的要求。     

Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise

In order to improve the accuracy of GNSS/INS working in GNSS-denied environment, a robust cubature Kalman filter (RCKF) is developed by considering colored measurement noise and missing observations. First, an improved cubature Kalman filter (CKF) is derived by considering colored measurement noise, where the time-differencing approach is applied to yield new observations. Then, after analyzing the disadvantages of existing methods, the measurement augment in processing colored noise is translated into processing the uncertainties of CKF, and new sigma point update framework is utilized to account for the bounded model uncertainties. By reusing the diffused sigma points and approximation residual in the prediction stage of CKF, the RCKF is developed and its error performance is analyzed theoretically. Results of numerical experiment and field test reveal that RCKF is more robust than CKF and extended Kalman filter (EKF), and compared with EKF, the heading error of land vehicle is reduced by about 72.4%.     

Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems

For a nonlinear system, the cubature Kalman filter (CKF) and its square-root version are useful methods to solve the state estimation problems, and both can obtain good performance in Gaussian noises. However, their performances often degrade significantly in the face of non-Gaussian noises, particularly when the measurements are contaminated by some heavy-tailed impulsive noises. By utilizing the maximum correntropy criterion (MCC) to improve the robust performance instead of traditional minimum mean square error (MMSE) criterion, a new square-root nonlinear filter is proposed in this study, named as the maximum correntropy square-root cubature Kalman filter (MCSCKF). The new filter not only retains the advantage of square-root cubature Kalman filter (SCKF), but also exhibits robust performance against heavy-tailed non-Gaussian noises. A judgment condition that avoids numerical problem is also given. The results of two illustrative examples, especially the SINS/GPS integrated systems, demonstrate the desirable performance of the proposed filter.     

基于单目视觉的移动机器人跟随

针对室外环境下移动机器人基于单目视觉对目标人实时跟随问题进行了研究,提出通过均值漂移算法对像平面目标的跟踪来实现目标定位。为了补偿摄像机运动造成目标在像平面的偏移,提出了以卡尔曼滤波器的估计值作为均值漂移算法的启动点,然后利用均值漂移算法获得最终位置;为了估计单目视觉下目标与机器人之间的距离,提出了一种借助于主颜色描述子和形状直方图的间接景深计算方法。室外实验表明该算法具有很好的实时性和鲁棒性,能有效实现复杂室外环境下对人的跟随。     

Control of gear shifts in dual clutch transmission powertrains

To achieve the best possible responses during shifting in dual clutch transmissions it is commonplace to integrate clutch and engine control, while the clutch is used to match speeds between the engine and wheels via reduction gears, poor engine control can lead to extended engagement times and rough/harsh shift transients. This paper proposes a method for combined speed and torque control of vehicle powertrains with dual clutch transmissions for both the engine and clutches. The vehicle powertrain is modelled as a simple four degree of freedom system with reduction gears and two clutches. Including a detailed clutch hydraulic model, comprising of the direct acting solenoids and clutch piston with the hydraulic fluid modelled as a compressible fluid. Powertrain control is realised through control of clutch solenoids and manipulation of the engine throttle input. Sensitivity study of clutch performance evaluating inaccurate torque estimation demonstrated variance in the response of the hydraulic system, with an indicative simulation of poor estimation resulting in increased powertrain vibration during and after shifting. Simulations are conducted to demonstrate the capacity for this method of engine and clutch control to further reduce shift transients developed in dual clutch transmission powertrains. The obtained results also show that the adoption of torque based control techniques for both the clutch and engine, which makes use of the estimated target clutch torque, significantly improves the powertrain response as a result of reduction in the lockup discontinuities.     

基于斜率约束和回溯搜索的水下多目标跟踪方法

针对复杂水域环境下的多目标跟踪问题,本文提出了一种基于斜率约束和回溯搜索的多目标跟踪方法。首先,基于方位测量数据和水下目标运动学分析,利用门限阈值的方法检测目标。然后,基于传统多假设跟踪算法框架设计一种新的斜率约束和共用量测的假设生成规则。在航迹中断时,通过回溯搜索的方法确定中断起始航迹点,利用容积卡尔曼滤波对中断航迹预测和补偿,同时对假设生成结果减枝,以达到降低算法空间复杂度的目的。试验结果表明:该方案能够实现多目标自动关联跟踪、中断航迹自动预测、自动航迹终止等任务,目标跟踪平均均方根误差0.594 4°,算法平均运行时间0.826 5 s。     

无转速计旋转机械升降速振动信号零相位阶比跟踪滤波

提出了一种用零相位滤波法和瞬时频率估计技术实现旋转机械升降速过程振动信号的阶比跟踪滤波的方法,和传统的以硬件实现的阶比跟踪滤波方法相比,该方法具有无需转速计和跟踪滤波器等硬件、用纯软件的方法实现和对原始采样信号不产生相位移动等优点。讨论了该方法的基本原理和算法,并在算法实现上提出了数据分段重叠滤波技术,可有效抑制一般分段数字滤波会产生的边缘效应。测试试验验证了该方法的正确性和有效性。     

A method of rational particle counting (author's transl)]

A method is described, which simplifies the counting of particles in a known volume. The counting of neurons of a brain region is used as an example for this procedure. The total volume is processed by histological serial sections. The total area of all sections of this volume is divided into counting squares by an ocular grid, from which we get a sample. This sample is described by the frequency distribution. The real number of particles in the volume is estimated by the values of the frequency distribution. The way of dividing, the size and the way of selection of these counting squares for a certain exactness of the estimation is determined. The method can be used for non-systematic distribution of particles in morphological structures.     

列车对列车无线通信中的信道特性分析

列车对列车(Train-to-train,T2T)通信能为现有车-地专网通信提供保障,其信道特性直接影响上层通信技术的应用.首先,根据铁路运营场景的空间分布结构和菲涅尔带理论提出一种适用于平原和长直隧道场景下追踪列车间直接通信的频率分配方案,并结合由降雨引起电波衰减的估算方法分析多频段无线信道的大尺度衰落.其次,推导T2T通信的最大多普勒频移计算公式,并通过射线跟踪法描述隧道内多径波,以分析小尺度衰落.最后,在同等速度条件下,仿真分析得出T2T通信低频段最大多普勒频移值明显低于车-地通信频移值.     

Coordinated shift control of nonsynchronizer transmission for electric vehicles based on dynamic tooth alignment

Multispeed transmissions can enhance the dynamics and economic performance of electric vehicles (EVs), but the coordinated control of the drive motor and gear shift mechanism during gear shifting is still a difficult challenge because gear shifting may cause discomfort to the occupants. To improve the swiftness of gear shifting, this paper proposes a coordinated shift control method based on the dynamic tooth alignment (DTA) algorithm for nonsynchronizer automated mechanical transmissions (NSAMTs) of EVs. After the speed difference between the sleeve (SL) and target dog gear is reduced to a certain value by speed synchronization, angle synchronization is adopted to synchronize the SL quickly to the target tooth slot’s angular position predicted by the DTA. A two-speed planetary NSAMT is taken as an example to carry out comparative simulations and bench experiments. Results show that gear shifting duration and maximum jerk are reduced under the shift control with the proposed method, which proves the effectiveness of the proposed coordinated shift control method with DTA.     

基于时间序列匹配的过山车定位法

针对过山车难以精准定位的问题,本文提出了一种基于时间序列匹配的过山车定位方法。该方法首先使用动态时间规整(DTW)对惯性测量单元(IMU)的实测与仿真数据进行序列匹配,得到位置估计结果。之后将估计结果作为观测量,在误差状态卡尔曼滤波器(ESKF)中修正IMU预测结果,得到精准的定位结果。为了提高估计结果的准确度,本文提出了分段重组动态时间规整(SRDTW)算法,解决了DTW的匹配失真问题。使用本文方法对过山车进行了定位实验,结果表明,使用Z向加速度和俯仰角进行序列匹配可得到较为准确的估计结果;ESKF滤波后的平均定位误差可达0.24 m,较估计结果的定位误差减小45.6%。     

基于非均匀快速傅里叶变换的正交频分复用水声通信多普勒估计与补偿方法

针对正交频分复用水声通信对多普勒频移敏感的问题,提出了一种基于非均匀快速傅里叶变换的正交频分复用水声通信多普勒估计与补偿算法.将第2类非均匀快速傅里叶变换引入正交频分复用水声通信中,利用非均匀快速傅里叶变换对接收信号进行多普勒因子网格补偿,通过稀疏贝叶斯学习获得水声信道估计,以水声信道的稀疏能量最小作为多普勒因子判断准...     

High-accuracy ultrasonic temperature measurement based on MLS-modulated continuous wave

Ultrasonic temperature measurement has the potential to improve measurement accuracy by increasing the length of a received signal due to its excellent performance with noise resistance. However, when the distance between the transmitter and receiver is limited, the received signal can be polluted by strong multiple echoes, which can significantly degrade temperature accuracy. This paper proposes a method for high-resolution ultrasonic temperature measurement. With the use of a maximum length sequence (MLS)-modulated continuous wave, the obstructive effect of echoes is effectively suppressed. A hybrid method is employed for accurate time-of-flight (TOF) estimation by incorporating both cross-correlation and phase shift (PS), which is the basis of highly accurate temperature measurement. The experimental results in distilled water show that the proposed method estimates TOF with a standard deviation of less than 0.3 ns, and temperature errors consistently remain within ±0.04 °C.     

A highly accurate ultrasonic ranging method based on onset extraction and phase shift detection

The opposite-type ultrasonic ranging application is widely used in spatial 3D coordinates measurement systems. The traditional phase shift (PS) estimation based on multi-frequency ultrasonic pulse is a highly accurate ranging method but has high requirement to the transducers and signal processing algorithm. This paper proposes a novel opposite-type ultrasonic ranging method with single frequency pulse. It can estimate the time of flight (TOF) roughly through extracting the signal’s onset based on self-correlation and correct the TOF accurately through detecting the phase shift between the transmission and reception signals. In order to reduce the noise disturbance to this algorithm, a new de-noising method based on wavelet decomposition is presented, and the de-noising effect is analyzed by MATLAB simulation. Finally, three separate ultrasonic ranging experiments were designed to validate the effects of wavelet de-noising, PS detection and temperature field compensation. The accuracy of distance measurement can achieve 0.5 mm for the distance up to 5000 mm.     

Non-stationary signal analysis based on general parameterized time–frequency transform and its application in the feature extraction of a rotary machine

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time–frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.     

基于贝叶斯估计的测试性仿真评估方法研究

经典测试性参数估计方法仅利用了样本所提供的关于总体的信息,没有利用关于待估统计量的其他信息,例如装备在研制阶段的测试性摸底试验以及丰富的专家数据;因此,这种经典估计方法在小样本情况下,很难真实反映装备的测试性水平。针对以上问题,本文提出了一种在获取仿真试验数据的前提下,进行综合装备先验信息测试性评估的方法,即基于贝叶斯估计的测试性水平估计,研究了测试性参数先验信息获取方法,给出了测试性参数的点估计和区间估计方法。     

结合特征定位噪声表征的单应矩阵精确鲁棒估计

针对基于特征匹配的单应矩阵估计方法的特征定位噪声的各向异性非同分布对其精度和鲁棒性的影响,提出了一种结合特征定位噪声表征的单应矩阵估计方法。该方法采用协方差矩阵来表征特征点定位噪声;基于协方差矩阵加权采样一致性(CWSAC)的内点检验方法来提高单应矩阵估计的鲁棒性。最后,提出一种单应矩阵高精度估计算法——协方差加权Levenberg-Marquardt(CW L-M)法。该方法结合协方差矩阵重新定义优化目标函数,提高了单应矩阵的估计精度。基于仿真数据和真实图像的实验表明,在相同定位噪声和内点比例条件下,本文算法的估计精度显著优于RANSAC(RANdom SAmple Consensus)、LMedS(Least Median of Squares),PROSAC(PROgressive SAmple Consensus)、M-SAC(M-estimator SAmple Consensus)和MLESAC(Maximum Likelihood SAmple Consensus)等传统算法,投影均方误差比次优方法降低了3%~21%。另外,本文方法对定位噪声和内点比例变化均具有较好的鲁棒性。     

相位补偿滤波方法在自动平衡系统中的应用

为了解决旋转机械在线自动平衡中信号相位提取问题,提出了一种无需整周期采样的相位检测算法。该算法基于互功率谱估计,具有算法复杂度低、抗干扰性好、精确度高和适用频率范围广等优点。在此基础上又提出了一种相位补偿滤波方法,使信号滤波造成的相位偏移得到补偿;该方法运算量低、精度高(误差小于1°)、可在线实时实现。仿真和实验表明,结合上述两种方法可准确、快速提取信号相位,从而使旋转机械在线自动平衡可以高效、准确、低成本的实现。