基于鲁棒H∞滤波的多站角度测量机动目标被动跟踪

建立了机动目标的多站被动红外搜索与跟踪（infrared search and tracking, IRST）系统的当前统计模型,基于该模型提出了机动目标跟踪的鲁棒H∞融合滤波算法。该算法将H∞滤波算法和集中融合跟踪算法相结合,对多站IRST测得的目标角度信息进行融合,可解决被动式跟踪系统的可观测性及非线性问题,以实现对目标较高精度的定位和跟踪。以三个观测站进行跟踪为例,对一个高机动目标进行了仿真研究,仿真结果表明,该滤波算法比扩展卡尔曼滤波（extended Kalman filter, EKF）算法有更高的跟踪性能,是IRST系统中一种有效的跟踪算法。     

Fault detection for networked systems subject to access constraints and packet dropouts

This paper addresses the problem of fault detection(FD) for networked systems with access constraints and packet dropouts.Two independent Markov chains are used to describe the sequences of channels which are available for communication at an instant and the packet dropout process,respectively.Performance indexes H∞ and H_ are introduced to describe the robustness of residual against external disturbances and sensitivity of residual to faults,respectively.By using a mode-dependent fault detection filter(FDF) as residual generator,the addressed FD problem is converted into an auxiliary filter design problem with the above index constraints.A sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities(LMIs).When these LMIs are feasible,the explicit expression of the desired FDF can also be characterized.A numerical example is exploited to show the usefulness of the proposed results.     

线性状态多时滞系统鲁棒故障诊断滤波器设计

研究一类具有外部扰动的不确定线性时滞系统的鲁棒故障诊断滤波器设计问题。通过引入一种广义坐标变换,使得线性连续状态多时滞系统变为输出灌入(outputinjection)系统;据此,引入一种体现残差对故障信号具有灵敏性同时对不确定性扰动具有鲁棒性的性能指标,应用H∞最优控制理论,借助线性矩阵不等式(LMI)技术设计系统的状态全维鲁棒故障诊断滤波器,并给出该滤波器问题解的存在条件和求解算法。最后给出一个仿真算例,仿真结果表明了该算法的有效性和可行性。     

SINS/CNS/GPS integrated navigation algorithm based on UKF

A new nonlinear algorithm is proposed for strapdown inertial navigation system (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation systems. The algorithm employs a nonlinear system error model which can be modified by unscented Kalman filter (UKF) to give predictions of local filters. And these predictions can be fused by the federated Kalman filter. In the system error model, the rotation vector is introduced to denote vehicle’s attitude and has less variables tha...     

分散鲁棒滤波器的设计

针对鲁棒滤波法计算量大和递推过程复杂的不足,通过等价推导,在线改变γf的值,设计了分散优化鲁棒滤波法,使得鲁棒滤波算法递推简单,避免了直接计算滤波增益阵,并减小了主滤波器计算负荷。将该算法应用于GPS/INS系统,仿真结果表明：该方法能在维持系统鲁棒性的同时又提高滤波精度,具有一定的工程实用价值。     

基于抗差UD分解滤波的导航星座整网定轨方法

针对我国导航星座的自主定轨问题,提出基于抗差UD(upper triangular matrix diagonal matrix)分解滤波的导航星座整网定轨方法。该方法对卫星轨道参数进行整网估计,通过对所有观测资料加权以避免观测粗差的影响,并利用UD分解算法来避免对协方差矩阵的直接求逆而导致的计算机舍入误差过大从而滤波发散。推导了整网定轨的数学模型,给出了抗差UD分解滤波的详细步骤。通过性能分析和仿真计算表明了该方法的可行性与有效性。     

Robust H∞ filtering for discrete-time systems with Markovian switching and time-delays

The robust H∞ filtering problem for uncertain discrete-time Markovian jump linear systems with modedependent time-delays is investigated. Attention is focused on designing a Markovian jump linear filter that ensures robust stochastic stability while achieving a prescribed H∞ performance level of the resulting filtering error system, for all admissible uncertainties. The key features of the approach include the introduction of a new type of stochastic Lyapunov functional and some free weighting matrix variables. Sufficient conditions for the solvability of this problem are obtained in terms of a set of linear matrix inequalities. Numerical examples are provided to demonstrate the reduced conservatism of the proposed approach.     

改进的强跟踪平方根UKF在卫星导航中应用

针对应用于受不确定性干扰和噪声影响的卫星自主导航系统中的无迹卡尔曼滤波（unscented Kalman filter,UKF）存在估计精度低、跟踪性能差和鲁棒性弱等缺陷,提出一种改进的强跟踪平方根UKF(strong tracking square-root UKF, STSRUKF)导航方法。该方法中利用星敏感器和光学导航相机设计出导航方案,并通过转换方程将间接量测量转换为观测量。针对平方根UKF（square-root UKF, SRUKF）在高阶系统中因为sigma点的零权值系数是负的或者数值计算误差太大时而可能造成滤波器发散问题,采用一种改良的平方根分解方法,改善了滤波器的稳定性。同时,基于强跟踪滤波器理论（strong tracking filters, STF）,引入多重自适应衰减因子调节协方差矩阵,使得滤波器具有强跟踪能力和克服系统模型不确定的鲁棒性,改善了滤波器的估计精度。将该方法应用于卫星自主导航系统中,实验仿真结果表明,相对于平方根UKF和STF,该方法不仅保证了系统的可靠性,还提高系统的导航精度和改善系统的鲁棒性及跟踪能力。     

Delay-dependent robust H∞ control for uncertain discrete time-delay fuzzy systems

The robust H∞ control problem of norm bounded uncertain discrete Takagi-Sugeno (T-S) fuzzy systems with state delay is addressed. First, by constructing an appropriate basis-dependent Lyapunov-Krasovskii function, a new delay-dependent sufficient condition on robust H∞-disturbance attenuation is presented, in which both robust stability and prescribed H∞ performance are guaranteed to be achieved. Then based on the condition, a delay-dependent robust H∞ controller design scheme is developed in term of a convex algorithm. Finally, examples are given to illustrate the effectiveness of the proposed method.     

不确定随机跳变时滞系统非脆弱H∞滤

针对一类具有马尔可夫跳变参数的It^o类型不确定随机时滞系统,讨论了该类系统的鲁棒非脆弱H_∞滤波问题。在被控对象及滤波器同时存在不确定性的情况下,闭环滤波误差系统渐近稳定,干扰抑制性能指标小于给定上界。通过构造一个Lyapunov Krasovskii泛函,应用It^o微分公式沿系统对其求微分,再运用线性矩阵不等式（linear matrix inequality, LMI）和It^o公式,给出了非脆弱滤波器存在的可解性条件。通过数值算例表明了该方法的有效性。     

基于强跟踪UKF的航天器自主导航间接量测滤波算法

针对广义卡尔曼滤波(extended Kalman filter, EKF)和无迹卡尔曼滤波(unscented Kalman filter, UKF)缺乏对系统异常的在线自适应调整能力、导致滤波器精度降低的问题,提出了一种将强跟踪滤波(strong tracking filter, STF)和UKF相结合的滤波算法,并进一步采用部分状态信息作为间接观测量,同时量测噪声方差阵实时调整,从而避免了对观测方程求取Jacobi矩阵的过程,使滤波器的设计得到简化。将该算法应用于航天器自主导航系统中,仿真结果表明,该算法在系统出现突变或缓变异常时,能够迅速检测出异常,在保证较高估计精度的同时,提高了系统的可靠性。     

基于Masreliez-Martin的鲁棒分数阶容积卡尔曼滤波算法及应用

针对具有非高斯量测噪声的分数阶离散时间非线性系统的状态估计问题, 提出一种基于Masreliez-Martin(简称为M-M)方法的鲁棒分数阶容积卡尔曼滤波器。在分数阶离散非线性动态系统基础上, 使用三阶容积原则推导了状态预测公式, 并使用M-M方法实现状态的量测更新, 构成了基于M-M方法的鲁棒分数阶容积卡尔曼跟踪算法。将提出的算法应用到再入目标的状态估计中, 仿真结果表明, 基于M-M方法的鲁棒分数阶容积卡尔曼滤波器优于分数阶无迹滤波器和分数阶容积卡尔曼滤波器。最后, 分析了不同程度的量测污染噪声对鲁棒分数阶容积卡尔曼滤波算法的估计性能影响, 验证了所提算法的鲁棒性。     

Robust H∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H∞ control for uncertain neutral stochastic systems with time-varying delay is discussed. The parameter uncertaintie is assumed to be time varying norm-bounded. First, the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method. Then, a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality (BMI), which ensures a prescribed stochastic robust H∞ performance level for the resulting closed loop system with nonzero disturbance input and for all admissible uncertainties. An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.     

IAE-adaptive Kalman filter for INS/GPS integrated navigation system

1 .INTRODUCTIONInertial navigation system(INS) and Global posi-tioning system ( GPS) are two major navigationsystems now widely usedfor marine applications a-round the world. Considering both systems pos-sess complementary working characteristics , abooming attention is focused on finding effectivemethods to combine the two different systems toconstituteintegrated navigation system with higheraccuracy and better performance .Information likeGPS position and velocity are often chosen as…     

奇异时滞系统的鲁棒故障检测和分离观测器

讨论了一类不确定奇异时滞系统的鲁棒故障检测和分离观测器(RDO)设计问题,设计所有的观测器使得它们的冗余信号对非故障因素具有鲁棒性,并设计每个观测器使其冗余信号对一组特定的故障不敏感而对其余故障敏感。给出了RDO存在的充分条件及有效的设计算法,并讨论了故障集合不同划分的RDO设计之间的关系,最后给出一具体算例来说明该方法的有效性。     

二次D稳定约束下不确定T-S模糊系统的L∞鲁棒可靠控制

针对一类受持续有界扰动的T-S不确定模糊系统,提出了考虑执行器故障的鲁棒可靠控制器设计方法。引入基于L_∞范数理论的鲁棒性能指标及二次D稳定的概念,给出了鲁棒可靠控制器存在的充分条件。通过求解线性矩阵不等式完成可靠控制器的设计,从而使系统即使在发生执行器故障的情况下仍能满足给定的L_∞性能指标,并且闭环系统二次D稳定。仿真实例表明了本方法的有效性。     

基于观测量扩充的捷联惯导快速初始对准方法

近似静止状态时捷联惯导系统可观测性较差,利用卡尔曼滤波完成初始对准需要较长时间。针对这一问题提出了一种基于观测量扩充的捷联惯导系统快速初始对准方法。在不改变系统状态方程的情况下,将速度误差和地球转速作为系统观测量。并根据观测量的扩展详细地推导了观测方程,进而利用扩展卡尔曼滤波完成捷联惯导系统初始对准。车载试验结果表明,与传统的卡尔曼滤波对准方法相比,新方法在保证初始对准精度的同时缩短了初始对准时间。     

不确定离散系统的有限时域鲁棒H∞滤波

研究了一类时变不确定离散系统的有限时域鲁棒H∞滤波问题。在系统不确定性满足范数有界的条件下,给出了有限时域鲁棒H∞滤波器存在的充分必要条件,并基于线性矩阵不等式技术给出了滤波器的构造性的设计方法。得到的滤波器对所有可容许不确定性，满足指定的性能指标。最后给出了仿真实例,仿真结果表明所设计的滤波器实现了设计要求。     

一种基于抗差滤波的行人导航算法研究

行人导航系统(pedestrian navigation system, PNS)通常采用全球定位系统(global positioning system, GPS)和航位推算(dead reckoning, DR)组合导航的方式进行定位,因此其定位精度易受GPS定位误差特别是定位粗差的影响。为了减小这种影响,提高行人导航系统定位精度,采用了一种基于抗差滤波的GPS/DR组合行人导航算法。该算法首先对DR系统误差建模,获得行人导航系统卡尔曼滤波模型,再通过GPS与DR系统观测量之差,估计当前观测噪声与先验统计特性的符合程度,利用等价权实时调整观测权值,以避免观测粗差对组合导航精度的影响。最后通过对实测数据的分析表明,在GPS定位误差较大或含粗差情况下,该方法较卡尔曼滤波算法能明显抑制定位误差的影响,将定位精度提高5 m左右,能够在不增加硬件的基础上有效提高GPS/DR组合行人导航精度。     

车辆自主导航系统的双滤波器模型及其导航算法

给出了车辆自主导航系统的双滤波器模型及其航位递推算法 ,在导航解算的每步递推中 ,先用航向滤波器进行航向捕获 ,再用航位滤波器进行航位捕获。这种方法利用两个线性滤波器分别进行航向 /航位估计 ,避免了常规导航算法由于观测方程线性化引起的模型误差 ,算法稳定性好 ,且计算量较小。现场跑车试验表明 ,给出的双滤波器模型及其算法能够获得满意的导航精度