Quaternion attitude and disturbance observer mass estimation with low-cost sensors for industrial vehicles with trailers

Information about the vehicle mass and ground slope is important for many assistance functions in road and logistics vehicles. In intralogistics, safe speed limits for tractors depend on both slope and trailer mass.This work presents an estimation procedure for the attitude of a vehicle and the mass of a trailer attached to it. The estimator works in two steps. First, the attitude is estimated using an extended Kalman filter based on acceleration and angular rate measurements complemented by a single track vehicle model. In the second step, this information is used together with velocity and motor torque data to estimate the trailer mass and friction coefficient. A Kalman filter based disturbance observer for parameter estimation is compared to a recursive least squares identification. The mass estimation is extended by a structural break test to detect sudden mass changes when hitching and unhitching trailers.Multiple variants of the estimation scheme are implemented on an intralogistics vehicle. The performance of the proposed attitude and mass estimation solutions is demonstrated in comparison to state of the art reference algorithms in a large number of experiments. Compared to state of the art estimators, the proposed estimator yields a median 54 % reduction of pitch estimation RMSE and 40 % reduction of the mass estimation error. The structural break detection is able to detect all instances of hitching and unhitching of trailers with few false positives.     

基于QEKF的四旋翼飞行器姿态估计

提出了一种基于四元数扩展卡尔曼滤波(QEKF)数据融合算法,应用于四旋翼飞行器的姿态估计。首先,用四元数表示航向姿态参考系统(AHRS)中的坐标旋转关系,获取飞行器的姿态信息;然后,结合扩展卡尔曼滤波算法,融合低成本的MPU9250中陀螺仪、加速度计、磁力计传感器的9轴原始输出数据,对飞行器的真实姿态进行跟踪估计;最后,通过MATLAB实验仿真,与互补滤波(CF)和梯度下降法(GD)算法进行比较,实验证明QEKF对姿态的估计更加精准。     

An Integrated Approach for the Estimation of Mobile Subscriber Geolocation

The continuous growth of wireless services market, fuels the need for precise location dependent services, leading researchers from academia and industry to reassess existing geolocation methods regarding accuracy and availability of position estimation. The proposed method for mobile subscriber geolocation utilizes key concepts from estimation theory and specifically the Kalman filter algorithm to determine an optimal estimate on the actual system state (which primarily includes location, velocity) based on the observations acquired by employing network- or terminal-based techniques, which are briefly presented and assessed thereafter. Given the proven limitations of individual techniques, the alternative strategies for fusion of data are outlined, the details of the operation of a fusion scheme based on the Kalman filter are discussed and the impact of the proposed work over conventional methodologies is quantified.     

IMM-based Kalman filter for channel estimation in UWB OFDM systems

Ultra-wide band (UWB) communication is one of the most promising technologies for high-data rate wireless networks for short-range applications. This paper proposes a blind channel estimation method namely Interactive Multiple Model (IMM)-based Kalman algorithm for UWB OFDM systems. IMM-based Kalman filter is proposed to estimate frequency selective time-varying channel. In the proposed method, two Kalman filters are concurrently estimating channel parameters. The first Kalman filter, namely the Static Model Filter (SMF) gives an accurate result when the user is static while the second Kalman filter namely the Dynamic Model Filter (DMF) gives an accurate result when the receiver is in moving state. The static transition matrix in SMF is assumed as an Identity matrix where as in DMF, it is computed using Yule–Walker equations. The resultant filter estimate is computed as a weighted sum of individual filter estimates. The proposed method is compared with other existing channel estimation methods.     

光纤陀螺的角加速度误差分析与实验研究

角加速度误差是光纤陀螺的一项动态误差,该误差会引起光纤陀螺捷联惯导系统的姿态误差,制约捷联惯性导航系统在高动态应用条件下的精度。针对这种情况,在光纤陀螺闭环控制模型的基础上建立了闭环光纤陀螺的角加速度误差模型,并分析了影响角加速度误差的几项重要因素,包括控制回路总增益及控制周期等;随后给出了减小该误差的方法。基于等效输入原理,通过在反馈阶梯波上叠加斜坡信号,分别在不同条件下对闭环光纤陀螺的角加速度误差进行了测试实验。实验结果表明,不同角加速度和控制回路总增益条件下的角加速度误差测试值与理论计算值基本一致,验证了该误差模型的正确性。     

New unbiased adaptive IIR filter: it’s robust and variable step-size versions and application to active noise control

This paper proposes a robust variable step-size adaptive IIR filter realized by a new bias-free structure (BFS). Unlike equation error (EQE) method that uses a desired signal contaminated with observation noise, the BFS employs a filter driven by the output of the plant estimate and this achieves a bias-free estimate of the denominator of the system function. In addition, the adaptation is made robust to the observation noise by the Griffiths’ LMS adaptation, which uses the cross-correlation estimate between the input and the desired signal for its adaptation gradient computation. A robust variable step-size adaptation is also realized by the Griffiths’ gradient. The proposed structure is referred to as BFSGV and has good modeling capability with improved convergence rate and reduced misadjustment. For system identification, the proposed BFSGV algorithm gives a 3 dB improvement in the performance index over EQE method. The proposed BFSGV has been applied to active noise control (ANC). The BSFGV structure is used for secondary path (SP) estimation, and for the main path (MP), BFS structure with step-size varied according to Okello’s method (BSFV) is used. The new ANC system for narrowband noise field is found to be having 4 times faster convergence rate and an additional noise reduction of 15dB over that FIR for MP and the EQE for SP. Further, the use of the proposed ANC IIR algorithm achieves computational savings compared to that of FIR. For the broadband noise field, the proposed method that uses BSFV for MP and BSFGV for SP provides 18 times faster convergence rate and 2.5 dB reduction in ANC error compare to that of the ANC using FIR for MP and the EQE for SP estimation.     

一种基于单轴正反旋转的惯性器件误差估计

为了提高捷联惯导导航精度,构建一种Kalman滤波模型来估计陀螺常值漂移和加速度计零偏。首先分析了载体作单轴正、反旋转运动时,捷联惯导的系统误差特性,然后以正、反旋转两过程中的姿态误差和速度误差为状态变量,以两过程中同一位置处的姿态误差差值和速度误差和值为观测变量,构建了一种Kalman滤波模型,来估计惯性器件常值误差;经可观测性分析,该模型是可观测的。仿真实验中,对于3个陀螺漂移均为0.1(°)/h、加速度计零偏均为9.78×10~(-3 )m/s~2的捷联惯导,陀螺漂移估计精度达到0.01(°)/h,水平方向加速计零偏估计误差均小于0.4×10~(-3 )m/s~2,实验证明该方案可行。     

Noise cross PSD estimation using phase information in diffuse noise field

Among various speech enhancement methods, two-microphone noise reduction systems are utilized for their low cost implementation and acceptable performance. Coherence-based methods are well known as efficient two-microphone noise reduction techniques. These techniques, however, do not work well when the received noise signals are correlated. Coherence-based methods can be improved when the cross power spectral density (CPSD) of input noises is available. In this paper, we propose a new method for estimating noise CPSD based on the assumption of a diffuse noise field. With this assumption, we estimate the noise CPSD using phase information. Then, the estimated noise CPSD is used to calculate a coherence-based gain filter which is then employed to enhance noisy signals. We compare the proposed phase-based noise CPSD estimation with a noise CPSD estimation technique based on a voice activity detector (VAD), both of which are herein separately employed in a two-microphone speech enhancement configuration. The comparison shows that the two-microphone speech enhancement scheme utilizing the proposed noise CPSD estimation technique outperforms the enhancement system using the VAD-based noise CPSD estimation.     

基于L BFGS的自适应模糊互补滤波

针对惯性测量单元噪声大及常规姿态解算算法精度不高的问题,提出了一种基于拟牛顿法（L-BFGS）的自适应模糊互补滤波（AFCF）算法。该方法利用L-BFGS对加速度计、磁力计进行寻优估计,并通过监测系统的运动等级、加速度计、磁力计的误差,运用模糊逻辑理论调控加权因子及增益权重,动态地调整互补滤波参数,实现姿态误差的动态补偿,优化姿态解算结果。经实验验证,系统静态误差在0.4°内;动态误差在1.3°内,且该系统能减少噪声的干扰及陀螺仪的漂移。     

Attitude control strategy for a camera stabilization platform

In this paper, an attitude control strategy for a 3-axis gimbaled platform used for the stabilization of film and broadcast cameras is presented. The attitude control strategy for the camera provides an alignment of the camera’s line of sight with a desired attitude, independent of the movements of the platform base. This control objective is achieved by a combination of a feedforward compensation of the disturbances induced by the moving base (the operator) and a feedback control of the orientation of the camera. The required attitude information is obtained by an attitude estimation strategy presented in [1] that fuses the measurements of two inertial measurement units. The derivation of the proposed control law utilizes a number of approximations tailored to the considered application. This allows to obtain an efficient but yet accurate attitude control concept. The very good accuracy and the practical feasibility of the overall control strategy are demonstrated by simulation and measurement results of a prototype platform.     

一类非线性时滞离散系统模糊H∞滤波器的设计

本文针对一类非线性、多时滞、干扰有界未知的离散系统进行H_∞模糊滤波器的设计.首先,利用T-S模糊模型来表达这个非线性、多时滞系统,并将建模误差,通过S-procedure,考虑到滤波器的设计中,建立基于T-S模糊模型的滤波器的存在条件,降低了滤波器设计的保守性.然后根据线性矩阵不等式(LMI)的性质将该模糊滤波器的设计转化为LMI的可行性问题,并采用凸优化技术的内点法求得LMI的可行解,设计出模糊滤波器.仿真结果表明,该方法是有效的.     

光纤光栅在微波光子滤波器中的应用

近年来,光纤光栅以其波长选择性好等特性得到了广泛的应用,随着人们对宽带通信的不断需求,微波光子学也在不断发展,微波光子滤波器更是成为该领域的热点之一,不断有利用光纤光栅构成微波光子滤波器的报道。综合评述了几种典型光纤光栅构成微波光子滤波器的结构,并分析比较了各自的功能特点和不足。     

光纤陀螺随钻测斜仪钻进中井眼轨迹测量方法研究

为提高光纤陀螺随钻测斜仪的井眼轨迹的测量精度,采用卡尔曼滤波组合的测量方法,对井斜、方位和工具面失准角进行估计。由于姿态失准角的估计精度与其可观测性密切相关,为了提高估计精度,文章分别在匀速、匀加速和匀速转动三种钻进运动状态下,采用分段线性定常系统(PWCS)和奇异值分解(SVD)的方法分析了姿态失准角的可观测性,并分析了钻进中井斜角和转动速率对姿态失准角估计精度的影响。由仿真结果可知,匀速钻进时,方位失准角不可观测;匀加速钻进时,方位失准角可观测且在水平井中可观测性最强,随着井斜角度增大,方位角、井斜角的测量精度逐渐提高;绕轴向匀速转动钻进时,方位失准角的可观测性和估计精度均优于匀速、匀加速钻进状态;角速率由0°/s增加到5°/s时,三个姿态失准角的估计精度均增大并逐渐趋于稳定。文中提出的轴向转动钻进运动可有效提高井眼轨迹的测量精度。     

An implementation of a programmable cascaded low-pass filter for a rotor flux synthesizer for an induction motor drive

This paper investigates a programmable cascaded low pass filter for the estimation of rotor flux of an induction motor, with a view to estimate the rotor time constant of an indirect field orientation controlled induction motor drive. Programmable cascaded low pass filters have been traditionally used in stator flux oriented vector control of the induction motor. This paper extends the use of this filter to estimate the rotor flux for the indirect field orientation control by generating rotor flux estimates from stator flux estimates. This is achieved by using a three-stage programmable cascaded low pass filter. The three-stage programmable cascaded low-pass filter investigated in this paper has resulted in excellent estimation of rotor flux in the steady-state and transient operation of an indirect field oriented drive. The estimated rotor flux data have also been used for the on-line rotor resistance identification with artificial neural network. Modeling and experiment results presented in this paper demonstrate this method of estimating rotor flux clearly.     

伯努利滤波器在纯角度跟踪场景中的应用

所获得信息只包含角度信息的传感器被称为纯角度传感器，基于纯角度传感器的目标跟踪被称之为纯角度跟踪（Bearings-only Tracking，BOT）。BOT是目标跟踪领域的重要课题，在被动目标跟踪场景中能够发挥重要作用。伯努利滤波器（Bernoulli Filter，BF）是贝叶斯框架内的最优单目标滤波器，可以求得目标的存在概率和完整的后验概率密度函数，并判断目标出现和消失。作者将伯努利滤波器应用于纯角度跟踪场景下的单目标跟踪问题，提出了一种纯角度跟踪伯努利滤波器。在所提出的滤波器中，将目标相对于传感器的角度及其变化率作为状态矢量，用于估计目标是否存在；若目标存在，估计其状态信息。同时，还给出了所提出滤波器的粒子滤波（Particle Filter，PF）实现方法。仿真结果显示，与普通伯努利滤波器相比，所提出的纯角度跟踪伯努利滤波器能够更好地判断目标是否存在，同时滤波器对于目标估计的误差也更小。因此，所提出的滤波器具有更好的跟踪性能和更高的跟踪精度，能够有效应用于被动跟踪场景中。     

Alpha稳定分布下基于RHMy滤波的MQAM信号码元速率估计方法

针对Alpha稳定分布噪声环境下,传统的MQAM信号码元速率估计方法性能恶化甚至完全失效的问题,本文结合了改进的Myriad类滤波与小波变换法的优点,提出一种基于递归混合Myriad滤波(Recursive Hybrid Myriad filter, RHMy)的高阶消失矩二次小波变换法对MQAM信号进行码元速率估计。首先采用RHMy滤波充分抑制噪声中的脉冲成分,再采用高阶消失矩小波估计码元速率。仿真结果表明,在Alpha稳定分布噪声环境中,相比于多尺度Haar小波变换法、分数低阶循环谱法与基于加权Myriad滤波(Weighted Myriad filter, WMy)的小波变换法,该方法有效的提高了低广义信噪比下的估计精度,同时在不同的脉冲噪声条件下具有较好的鲁棒性。      

Improving differential detection of MDPSK by nonlinear noiseprediction and sequence estimation

A new technique is proposed to improve the performance of differential detection (DD) of M-ary differential phase-shift keying (MDPSK) significantly, applying sequence estimation. In order to obtain an appropriate representation of the received signal, a nonlinear time-variant finite impulse response or infinite impulse response prediction-error filter is used. For both filter structures the optimum coefficients are derived, assuming transmission over an additive white Gaussian noise (AWGN) channel. Delayed decision-feedback sequence estimation (DDFSE) is employed to estimate the transmitted symbol sequence. It is shown by simulations that even for decision-feedback equalization, which is a simple special case of DDFSE, a significant performance improvement of conventional DD under AWGN conditions results. In contrast to other noncoherent low-complexity receivers proposed in literature, this receiver is very robust under flat fading (Rayleigh and Ricean) conditions     

消除FOG—ARW对初始对准影响的研究

光纤陀螺(FOG)作为光学惯性敏感器,与传统机械陀螺相比,具有角度随机游走(ARW)等一些特有的性能指标,ARW对导航系统性能具有重要影响。从光纤陀螺的光路、电路结构分析随机游走产生的机理,并从数学的角度阐述角度随机游走的定义;分析角度随机游走对初始对准的影响;提出利用卡尔曼滤波器有效消除角度随机游走对初始对准影响的方案并通过仿真验证了此方案的有效性。     

在脉冲噪声环境中用于快衰信道估计的改进型算法

该文分析了在存在噪声干扰的情况下,进行估计快衰信道的方法。在无线通信系统中,快衰信道可以采用AR(Auto-Regressive)模型进行预测,而LS (Least Square)算法和自适应Kalman滤波器可以分别对AR模型的参数和信道的冲激响应进行估计,但是这两种算法对噪声干扰非常敏感。该文提出改进型的RLM算法和Kalman 滤波器,并在存在噪声的情况下,使用它们并行对AR参数和信道的冲激响应进行联合估计。仿真结果显示：相比于传统的算法,改进后的算法在联合估计信道时,提高了抵抗大脉冲干扰的能力,加快了待估的参数的收敛速度。     

联邦滤波在光纤陀螺捷联惯导系统传递对准中的应用

对舰载武器光纤陀螺捷联惯导系统相对舰船综合导航信息系统的动基座传递对准技术进行了研究,提出了将挠曲变形、时间延迟作为系统状态,并给出了系统状态方程和量测方程。采用联邦滤波作为信息融合算法的传递对准方法,对系统方程中的状态变量进行了可观测度分析,并推导了速度、姿态匹配子滤波器方程及主滤波器方程。最后进行了仿真试验,试验结果表明:该传递对准方法使方位精度提高20%以上;该方法能够有效解决舰船条件下光纤陀螺捷联惯导系统的传递对准。