Discrete-time observability and estimability analysis for bearings-only target motion analysis

Observability in the context of bearings-only tracking (BOT) is still the subject of important literature. Different from previous approaches, where continuous-time analysis was considered, our approach relies on discrete-time analysis. It is then shown that this allows us to use directly and efficiently the simple formalisms of linear algebra. Using the direct approach, observability analysis is essentially reduced to basic considerations about subspace dimensions. Even if this approach is conceptually quite direct, it becomes more and more complex as the source-encounter scenario complexity increases. For complex scenarios, the dual approach may present some advantages essentially due to the direct use of multilinear algebra. New results about BOT observability for maneuvering sources are thus obtained. Observability analysis is then extended to unknown instants of source velocity changes. Even if observability analysis provides thorough insights about the algebraic structure of the BOT problem, the optimization of the observer maneuvers is essentially a control problem. Basic algebraic considerations prove that a relevant cost functional for this control problem is the determinant of the Fisher information matrix (FIM). So, a large part of this work is devoted to the analysis of this cost functional. Using multilinear algebra, general approximations of this functional are given. In order to involve only directly estimable parameters, the source bearing-rates are examined. Using these approximations, a general framework for optimizing the observer trajectory is derived which allow us to approximate the optimal sequence of controls. It is worth stressing that our approach does not require the knowledge of the source trajectory parameters and is still valid for a maneuvering source.     

非线性动态逆神经元解耦飞行控制方法

 提出一种非线性动态逆神经元控制系统设计方法，并成功的将其应用于某战斗机非线性解耦控制问题。该方法的基本思想是采用神经元网络建立非线性被控对象的动态逆模型，将被控对象转化为伪线性系统，并用现代控制系统综合设计方法对神经元伪线性系统进行闭环优化设计。给出的战斗机非线性动态逆神经元解耦飞行控制系统的仿真结果显示出人工神经元网络作为非线性动态逆控制单元所具有的潜在能力。     

Bearings-only and Doppler-bearing tracking using instrumentalvariables

In bearings-only tracking (BOT) or Doppler and bearing tracking (DBT), both common passive sonar problems, the measurement equations are nonlinear. To apply the Kalman filter, it is necessary either to linearize the equations or to embed the nonlinearities into the noise terms. The former sometimes leads to filter divergence, while the latter produces biased estimates. A formulation of BOT and DBT which has a constant state vector and simplifies the tracking problem to one of constant parameter estimation is given. The solution is by the instrumental variable method. The instrumental variables are obtained from predictions based on past measurements and are therefore independent of the present noisy measurements. The result is a recursive unbiased estimator. The theoretical developments are verified by simulation, which also shows that the formulation leads to near optimal estimators whose errors are close to the Cramer-Rao lower bound (CRLB)     

Nonlinear filtering: A hybrid approximation scheme

This paper is concerned with nonlinear filtering schemes for systems which allow non-Gaussian noise. Using the most probable trajectory (MPT) approach, a finite-dimensional recursive hybrid filtering scheme is derived. By appropriately selecting a switching process, a linear hybrid system can be obtained that approximates the original nonlinear system. Then the MPT approach is used to obtain the hybrid filtering schemes for the nonlinear systems. Numerical experiments are carried out and reported     

永磁同步电机无传感器转子位置观测器研究

永磁同步电机的运动是一个强耦合非线性动态过程,旋转高频电压注入下 的电机模型存在建模误差,数据采集存在测量噪声和系统噪声,采用传统的线性控制理 论难以达到要求。提出了以不依赖于准确数学模型的广义预测控制算法为基础的转子位 置观测器,可有效提高转子位置检测精度,增强抗干扰能力。仿真实验结果表明,在存 在建模误差和噪声的情况下,基于广义预测控制算法位置观测器的旋转高频注入法可准 确追踪转子位置。     

Simultaneous state and actuator fault estimation for satellite attitude control systems

In this paper, a new nonlinear augmented observer is proposed and applied to satellite attitude control systems. The observer can estimate system state and actuator fault simultaneously. It can enhance the performances of rapidly-varying faults estimation. Only original system matrices are adopted in the parameter design. The considered faults can be unbounded, and the proposed augmented observer can estimate a large class of faults. Systems without disturbances and the fault whose finite times derivatives are zero piecewise are initially considered, followed by a discussion of a general situation where the system is subject to disturbances and the finite times derivatives of the faults are not null but bounded. For the considered nonlinear system, convergence conditions of the observer are provided and the stability analysis is performed using Lyapunov direct method. Then a feasible algorithm is explored to compute the observer parameters using linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed approach is illustrated by considering an example of a closed-loop satellite attitude control system. The simulation results show satisfactory perfor-mance in estimating states and actuator faults. It also shows that multiple faults can be estimated successfully.     

Neighboring optimal guidance for aeroassisted orbital transfer

A neighboring optimal guidance scheme for a nonlinear dynamic system is devised with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory is determined. Then, taking modeling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme is devised. Assuming the additive character of the stochastic effects, the optimal trajectory is approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical aeroassisted orbital transfer vehicle     

基于未知输入观测器的非线性动态系统故障估计

针对一类受扰非线性动态系统的执行器故障估计问题,提出一种未知输入观测器来实现故障估计。首先,通过坐标变换将原系统转化为合适的形式;其次,采用线性矩阵不等式与Lyapunov泛函分别设计H_∞输出反馈控制器和未知输入观测器,在此基础上实现对系统中执行器故障的渐近估计;最后,通过机械臂系统仿真分析并验证了所提方法的有效性。与已有方法相比,所提方法不要求故障可导,也不要求故障或干扰上界已知,因此易于在工程实际中实现对非线性系统执行器故障的估计。     

UKF方法及其在方位跟踪问题中的应用

采用UKF(Unscented Kalman Filter)方法处理了平面内地面站对目标的方位跟踪的估计问题。目标的位置和速度由选定的高斯分布采样点来近似，在每个更新过程中，采样点随着状态方程传播并随着非线性测量方程变换，由此不但得到目标位置和速度的均值及较高的计算精度，而且避免了对非线性方程的线性化过程。仿真结果表明，UKF方法比传统的扩展卡尔曼滤波(EKF)算法有更高的估计精度，并能有效地克服非线性严重时，方位跟踪问题中很容易出现的滤波发散问题。     

Optimal measurement scheduling for state estimation

We consider the problem of optimal allocation of measurement resources, when: (1) the total measurement budget and time duration of measurements are fixed, and (2) the cost of an individual measurement varies inversely with the (controllable) measurement accuracy. The objective is to determine the time-distribution of measurement variances that minimizes a measure of error in estimating a discrete-time, vector stochastic process with known auto-correlation matrix using a linear estimator. The metric of estimation error is the trace of weighted sum of estimation error covariance matrices at various time indices. We show that this problem reduces to a nonlinear optimization problem with linear equality and inequality constraints. The solution to this problem is obtained via a variation of the projected Newton method. For the special case when the vector stochastic process is the state of a linear, finite-dimensional stochastic system, the problem reduces to the solution of a nonlinear optimal control problem. In this case, the gradient and Hessian with respect to the measurement costs are obtained via the solution of a two-point boundary value problem and the resulting optimization problem is solved via a variation of the projected Newton method. The proposed method is illustrated using four examples     

Coordinated target localization base on pseudo measurement for clustered space robot

This paper presents a coordinated target localization method for clustered space robot.According to the different measuring capabilities of cluster members,the master-slave coordinated relative navigation strategy for target localization with respect to slavery space robots is proposed;then the basic mathematical models,including coordinated relative measurement model and cluster centralized dynamics,are established respectively.By employing the linear Kalman flter theorem,the centralized estimator based on truth measurements is developed and analyzed frstly,and with an intention to inhabit the initial uncertainties related to target localization,the globally stabilized estimator is designed through introduction of pseudo measurements.Furthermore,the observability and controllability of stochastic system are also analyzed to qualitatively evaluate the convergence performance of pseudo measurement estimator.Finally,on-orbit target approaching scenario is simulated by using semi-physical simulation system,which is used to verify the convergence performance of proposed estimator.During the simulation,both the known and unknown maneuvering acceleration cases are considered to demonstrate the robustness of coordinated localization strategy.     

Passive tracking scheme for a single stationary observer

While there are many techniques for bearings-only tracking (BOT) in the ocean environment, they do not apply directly to the land situation. Generally, for tactical reasons, the land observer platform is stationary; but, it has two sensors, visible and infrared, for measuring bearings and a laser range finder (LRF) for measuring range. There is a requirement to develop a new BOT data fusion scheme that fuses the two sets of bearing readings, and together with a single LRF measurement, produces a unique track. This paper first develops a parameterized solution for the target speeds, and then heading, prior to the occurrence of the LRF measurement, when the track is unobservable. At, and after the LRF measurement, a BOT, formulated as a least squares (LS) estimator, then produces a unique LS estimate of the target states. Bearing readings from the other sensor serve as instrumental variables in a data fusion setting to eliminate the bias in the BOT estimator. The result is an unbiased and decentralized data fusion scheme. Results from two simulation experiments have corroborated the theoretical development and show also that the scheme is optimal.     

气浮支承式触针测量系统径向动态性能研究

触针表面形貌测量仪是生产科研中应用广泛的仪器,杠杆式触针由于其结构原因,在测量时会产生非线性误差,影响测量结果的精度。介绍了一种气浮触针式测量传感器,触针轴运动方向与位移测量方向一致,有效地避免了非线性误差;在研究中建立了气浮支承式触针测量系统的运动模型,分析了测量系统的动静态特性,研究了影响气浮支承径向动态性能的因素,进行了径向刚度和动态参数的理论仿真模拟,并通过动态特性试验测试和分析得到传感器最大扫描频率为125Hz;搭建了气浮触针式表面形貌测量系统并进行测量试验,得到传感器测量的相对误差为0.8%。     

航天器姿控系统的PD型学习观测器故障重构

针对满足Lipschitz条件的航天器姿态控制系统这一非线性系统中存在的执行器加性故障、空间干扰与测量噪声问题,提出了基于PD型迭代学习观测器的故障重构方法。该方法具有期望的鲁棒性能指标,能够在系统存在空间干扰与测量噪声情况下实现对突变故障与时变故障等故障类型的精确重构。基于线性矩阵不等式技术给出系统化PD型迭代学习观测器的设计方法,并根据Lyapunov稳定性理论对上述设计方法的稳定性条件进行了理论证明,同时利用鲁棒技术抑制空间干扰与测量噪声对执行器故障重构的影响,通过线性矩阵不等式工具箱求解观测器参数矩阵。最后,将该方法应用到航天器姿态控制系统中,仿真结果证明了该方法的有效性。     

传感器位置误差条件下的约束总体最小二乘时差定位算法

 现代定位系统中,传感器往往被安放在运动平台上,其位置无法精确得知,存在估计误差,将严重影响对目标的定位精度。针对这一问题,提出基于约束总体最小二乘(CTLS)的到达时差(TDOA)定位算法。首先通过引入中间变量,将非线性TDOA定位方程转化为伪线性方程,再利用CTLS技术,全面考虑伪线性方程所有系数中的噪声。在此基础上推导了定位方程的目标函数,再根据牛顿迭代方法,进行数值迭代,快速得到精确解。采用一阶小噪声扰动分析方法,对该算法的理论性能进行了分析,证明了算法的无偏性和逼近克拉美-罗下限(CRLB)。仿真实验表明,该算法克服了现有总体最小二乘(TLS)算法不能达到CRLB、两步加权最小二乘(two-step WLS)算法在较高噪声时性能发散的缺陷,在较高噪声时定位精度仍然能达到CRLB。     

Periodic acoustic source tracking using propagation delayed measurements

There exist a large class of acoustic sources which have an underlying periodic phenomenon. Unlike the well-studied Bearings-Only Tracking(BOT) of an aperiodic acoustic source,this paper considers the problem of tracking a periodic acoustic source. For periodic acoustic tracking, the signal emission time is known. However, the true measurement reception time is unknown because it is corrupted by noise due to propagation delay. We augment the sensor’s signal reception time onto bearing measuremen...     

Non-linear aircraft flight path reconstruction review and new advances

Aircraft parameter identification techniques have become accepted as indispensable tools in the evaluation of prototype- and derivative aircraft in flight. Applications include estimation of stability- and control derivatives in the linearized equations of motion, synthesis of nonlinear aerodynamic and propulsion models in the context of performance certification and incorporation of information from dynamic flight test manoeuvres in a priori nonlinear flight simulation models. A variety of techniques in the time- as well as the frequency domain have been applied in the past. One of the successful techniques is the so-called two-step method (TSM) in which the original state-parameter estimation problem is decomposed into a nonlinear state/parameter estimation or reconstruction problem and a subsequent linear parameter identification problem. In the literature, the first step of the TSM is often referred to as `flight path reconstruction'. The present paper focuses on the first step of the TSM. After a derivation of the system models describing the flight path relative to a flat earth as well as a spherical and rotating earth, and observation models for air data and GPS, the flight path reconstruction problem is introduced. Requirements with respect to type and quality of flight test transducers are discussed. Next follows an overview of different approaches to the solution of the flight path reconstruction problem with emphasis on Kalman filter/smoother and Maximum Likelihood methods. A new adaptive algorithm is presented, the Modified Recursive Maximum Likelihood Adaptive Filter (MRML) which is shown to be significantly more robust with respect to initialisation errors than earlier methods. A reconstructibility analysis is presented for different transducer combinations. Numerical examples are presented based on simulated as well as actual flight test data. Flight results are given of the flight path reconstruction part of an on-line pseudo real-time application of the TSM. The paper ends with concluding remarks.     

对卫星目标的仅测角天基单站无源定位可观测性分析

可观测性分析是无源定位与跟踪系统的前提和基础。由于卫星运动系统方程是状态变量的隐函数形式,以及观测方程的非线性,使得对卫星目标仅测角无源定位的可观测性研究难度较大。鉴于此,从伪线性化角度对非线性系统方程进行改造,推导了关于状态变量的显性系统状态方程,对仅测角条件下的单星对星无源定位系统进行了可观测性分析,为进一步研究仅测角单星对星的无源定轨跟踪提供了理论基础。最后给出了仿真实例,验证了理论分析的正确性。     

具有未知输入干扰的观测器设计

提出一种全阶比例积分观测器。该观测器包含有估计误差的比例和积分回路,可同时得到状态和未知输入估计。分析了比例积分观测器的结构和估计性能,给出并证明了其存在条件,由于存在条件弱于未知输入观测器,该比例积分观测器可以更广泛地应用于基于观测器的技术方案。通过一个飞行器线性化模型,进行了比例积分观测器设计。仿真结果表明,比例积分观测器的估计性能优于常规 Luenberger观测器     

Nonlinear robust observer design for strapdown INS in-flight alignment

A nonlinear observer is proposed for a strapdown inertial navigation system (SDINS) in-flight alignment problem using an H/sub /spl infin// filter Riccati equation and a freedom parameter. The proposed observer improves the filtering stability, convergence, and performance. The characteristics of the observer are analyzed using a Lyapunov function. Simulation results demonstrate a significant reduction in alignment errors by employing the proposed nonlinear observer. The observer is developed in general such that it can be applied to estimating nonlinear systems other than the SDINS in-flight alignment.