飞行数据处理的非线性鲁棒滤波技术

研究了飞机飞行试验数据处理中的非线性鲁棒滤波技术,分析给出了实际飞行条件了一种飞机运动的新模型,它是含不确定参数项的非线性模型,同时给出了该不确定参数项的解析的表达形式,然后研究了对应于此类非线不确定系统的鲁棒滤波算法,得到了该滤波问题的充分解,并对该解进行扩展线性化处理,得么了一个较易实现的扩展鲁棒滤波算法,最后利用该算法对实际的数据进行了处理,结果表明,所提出的算法是切实可行的。     

离散系统LMI滤波技术

给出了一种离散系统最优滤波器的线性矩阵不等式（ＬＭＩ）设计方法。在系统干扰噪声能量有界情况下,将有约束的滤波问题转换为无约束的最优状态估计问题。利用ＬＭＩ方法给出了最优无偏滤波器存在的充分必要条件,所得滤波器的阶数小于系统状态个数。将ＬＭＩ方法应用于飞机飞行试验数据处理中,分析了实际飞行条件下飞机运动的模型,并对该模型进行扩展线性化处理,得到了一个较易实现的ＬＭＩ滤波算法。仿真结果表明,所提出的算     

GPS/INS组合导航系统自适应滤波算法与仿真研究

随着组合导航系统应用环境的日趋复杂，给噪声统计特性的准确描述带来困难，这将造成Kalman滤波器不稳定甚至发散。首先对目前解决此问题常用的自适应滤波方法进行了总结和分析，在此基础上，给出了基于滤波收敛性判据，结合Sage-Husa自适应滤波和强跟踪Kalman滤波的改进自适应滤波算法。最后以GPS／INS组合导航系统为例进行了计算机仿真，结果表明：该算法可有效抑制滤波发散，具有较大范围的自适应能力。     

Optimum Reset of Ship's Inertial Navigation System

Optimum linear filter and control theory is applied to the practical problem of supplementing an inertial navigation system with discrete reference information. The information takes the form of position obtained from Loran C or Decca, for example, and occasional azimuth fixes obtained from star sightings. In particular, optimum use of this information is discussed for the Ship's Inertial Navigation System (SINS) installations intended for missile carrying submarines and warships. A model representative of the SINS dynamics is formulated appropriate for application of optimum filter and control theory. Interpretation of the optimum control dictated in part by the augmented SINS model is discussed. Simulation studies that show the relative transient behavior and the stabilizing effect of the closed-loop filter and control processes are also presented.     

Mixture Reduction Algorithms for Point and Extended Object Tracking in Clutter

The Bayesian solution to the problem of tracking a target with measurement association uncertainty gives rise to mixture distributions, which are composed of an ever increasing number of components. To produce a practical tracking filter, the growth of components must be controlled by approximating the mixture distribution. Two mixture reduction schemes (a joining algorithm and a clustering algorithm) have been derived for this purpose. If significant well spaced mixture components are present, these techniques can provide a useful improvement over the probabilistic data association filter (PDAF) approach, which reduces the mixture to a single Gaussian component at each time step. For the standard problem of tracking a point target in uniform random clutter, a Monte Carlo simulation study has been employed to identify the region of the problem parameter space where significant performance improvement is obtained over the PDAF. In the second part of this paper, the formal Bayesian filter is derived for an extended target consisting of an array of measurement sources with association uncertainty. A practical multiple hypothesis filter is implemented using mixture reduction and simulation results are presented.     

再论联邦滤波在组合导航中的应用可行性

在联邦滤波算法中，针对子滤波器存在私有状态从而导致全局状态信息融合估计为次优估计的问题，通过一个简单的3维状态、2维量测系统的数值仿真以及速度+姿态传递对准组合导航仿真，验证了联邦滤波的次优估计结果误差太大，难以满足实际系统的高精度滤波需求。联邦滤波估计的次优程度没有经过严格证明，且难以证明，因而存在应用风险。对于以精度为主要性能指标的组合导航系统，不建议采用联邦滤波算法，否则其精度损失不足以弥补其带来的计算量降低和容错性提高的优势。     

A Stratified Statistical Filter with Nonlinear Application

This paper introduces a statistical filter (or, more strictly, a filtering algorithm) which has intended application in the area of nonlinear systems. Within this context, the filter enables one to investigate the convergence effects produced by varying the initial estimates associated with the respective state variables, together with the various system parameters. The present algorithm is not intended to replace the more powerful optimal statistical filters used in linear theory, but rather to provide a simulation tool which can readily be applied to a given nonlinear system. The application considered in this paper bears a similarity to a tracking problem which might be encountered by an optical device, where angular information is the primary observable quanity. In this particular application, angular observations are available, and statistical estimates are desired for a position variable, together with an unknown parameter. The application is introduced primarily for the purpose of demonstrating the behavior of the filter when applied to a relatively simple nonlinear system.     

Feedback median filter for robust preprocessing of glint noise

Glint noise may arise in a target tracking system. The non-Gaussian behavior of glint noise can severely degrade the tracking performance. Measurement preprocessing at the front-end of the tracker is an effective method to reduce glint noise. The preprocessor proposed by Hewer, Martin, and Zeh (1987), which used the computationally intensive M-estimator, may not be suitable for practical implementation. An alternative method employing the median filter is studied here. The median filter is well known for its simplicity and robustness. However, the efficiency of the median filter can be seriously degraded if input samples are not identically distributed. This is what we may encounter in the tracking problem. A feedback median filter is then proposed to overcome this impediment without substantially increasing complexity. Simulations show that the new preprocessor can greatly improve tracking performance in the glint noise environment.     

Feedback Realization of a Continuous-Time Optimal Filter

Another derivation of a continuous-time optimal linear filter is presented. Using this result as a point of departure, a feedback version of this continuous filter is postulated and shown to be optimal in the limit as the ``feedback gain' becomes infinite. It is then demonstrated that the need for this infinite feedback gain can frequently be eliminated. This feedback realization of the continuous optimal filter has application to the problem of optimally mixing two or more redundant signals, each contaminated by random noise. The feedback configuration has the advantages of simplicity and the bounding of otherwise troublesome very large errors. A simple example is given of the mixing of two (velocity) references each having exponentially correlated error.     

在飞行中进行风场估计

在飞行中如何获得较精确的风场信息,对于飞行导航、控制和管理系统的研究都是一个重要的、急需解决的问题。目前飞机上无高精度的风测量手段.为此,本文将卡尔曼滤波技术应用到风场估计中去,并提出了一个简单实用的风模型。仿真结果表明该方案是成功的。本文属某无人机航迹控制研究计划的一部分.从这一工程实例出发,详细说明了利用卡尔曼滤波技术进行风场估计的全过程,其中包括飞机地速的估计,风测量精度分析等内容。     

某型机载惯性/卫星/大气多信息融合MEMS航姿系统的设计与实现

针对机载MEMS航姿系统中器件精度低且易受干扰导致其姿态性能降低的问题,提出了一种基于大气/卫星信息辅助的航姿系统融合方案。构建了多源传感信息辅助下的综合航姿系统方案,所设计系统具有多种工作运行模式,可根据传感器可用状态实现滤波器的无缝切换,建立了组合导航系统状态和量测模型,采用Kalman滤波方法实现多源信息的融合与估计,并开展了原理样机的跑车试验。试验结果表明,所设计的融合方案能有效保障航姿系统的可靠性与精度,具有较高的工程应用价值。     

SINS/BDS紧组合系统中自适应 两阶段扩展卡尔曼滤波

在实际应用中，以伪距/伪距率为观测量的SINS/BDS紧组合导航系统，存在量测噪声的统计特性与实际不相符的情况，传统扩展卡尔曼滤波（EKF）方法无法有效解决这一问题，从而引起滤波误差增大。提出了一种SINS/BDS紧组合导航系统的GDOP估算及在线估计量测噪声的自适应两阶段EKF（ATEKF）方法，该方法使用经过紧组合修正后的SINS输出的位置，并结合星历数据中提供的卫星位置求解GDOP。在此基础上，利用GDOP值以及新息，实现了紧组合导航系统的量测噪声方差阵（Rk）的在线实时估计，从而达到自适应滤波的效果，改善导航精度。     

Effects of a Finite-Width Decision Threshold on Binary CPSK and FSK Communication Systems

The function of the receiver in a binary digital communication system is to make a binary (?space?, ?mark? or ?"0?, ?1?) decision by comparing the signal values from the mark and space filters (or correlators) at known successive time intervals (?bit? or ?baud? time intervals). When the signal value out of the mark filter is greater than that out of the space filter, it is decided that mark or 1 is transmitted, and vice versa. It is of fundamental importance to know the exact instant of time at which the two filter outputs are to be compared. This is the problem of synchronization between the transmitter and the receiver. In this paper, we assume a system that is perfectly synchronized. In a practical system, the difference between the two filter outputs must differ from a threshold by some finite amount in order to cause the device to respond reliably. The examination of the effects of this dead zone (finite-width decision threshold) on digital transmission systems is of important practical interest. Its effects on binary differentially coherent phase-shift-keying, and m-level phase-shift-keying systems have been investigated previously. In this paper we consider its effects on binary coherent phase-shift-keying (CPSK), coherent orthogonal (CFSK), and noncoherent orthogonal (NCFSK) systems. The probability of bit error and the channel capacity of each system is obtained in terms of the dead zone threshold.     

Kalman filtering with state equality constraints

Kalman filters are commonly used to estimate the states of a dynamic system. However, in the application of Kalman filters there is often known model or signal information that is either ignored or dealt with heuristically. For instance, constraints on state values (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. A rigorous analytic method of incorporating state equality constraints in the Kalman filter is developed. The constraints may be time varying. At each time step the unconstrained Kalman filter solution is projected onto the state constraint surface. This significantly improves the prediction accuracy of the filter. The use of this algorithm is demonstrated on a simple nonlinear vehicle tracking problem     

EMI滤波器控制传导干扰实验与分析

应用理论分析和实验总结出来的关于共模和差模传导干扰信号的分布规律,分析电子设备电源线上存在的干扰信号的特点,试用不同网络结构的电磁干扰(EMI)滤波器来控制电子设备在在的传导干扰电平,使之符合有关电磁兼容性(EMC)标准规定的极限值为例,说明EMI滤波器设计和应用中碰到的某些实际问题,对指导用EMI滤波器来解决电子设备存在的电磁干扰和进行EMC试验很有实际意义。     

智能航迹推算系统的研究

提出了一种新模糊滤波法用于补偿磁罗盘测量值中的低频干扰。在此基础上 ,进一步提出了一种新的滤波方法 :模糊 -补偿滤波法 ,以消除磁罗盘测量值中各种干扰的影响。仿真表明 :在较长的时间内 ,采用模糊 -补偿滤波法的航迹推算系统的航向估值误差和位置误差均较小。     

一种有效的抑制压电陀螺动态误差的方法

提出了一种基于小波滤波的补偿压电陀螺动态误差的方法.与自适应卡尔曼滤波、IIR低通滤波方法在实际工程中应用的比较和大量的跑车实验表明,该方法能够有效去除压电陀螺动态误差噪声干扰,提高压电陀螺使用精度.     

A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

It is common for aircraft to encounter atmospheric turbulence in flight tests. Turbulence is usually modeled as stochastic process noise in the flight dynamics equations. In this paper, parameter estimation of nonlinear dynamic system with both process and measurement noise was studied, and a practical filter error method was proposed. The linearized Kalman filter of first-order approximation was used for state estimation, in which the filter gain, along with the system parameters and the initial states, constituted the parameter vector to be estimated. The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method, and the sensitivities of observations to unknown parameters were calculated by finite difference approximation. Some practical aspects of the method application were discussed. The proposed filter error method was validated by the flight simulation data of a research aircraft. Then, the method was applied to the flight tests of a subscale aircraft, and the aerodynamic stability and control derivatives were estimated. All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach. It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.     

Unsupervised Tracking of Maneuvering Vehicles

The design of adaptive filters for the tracking of high-performance maneuvering targets is a fundamental problem in real-time surveillance systems. As is well known, a filter which provides heavy smoothing can not accurately track an evasive maneuver, and conversely. Consequently, one is led to the consideration of adaptive methods of filter design. This paper presents an improved self-adaptive filter algorithm for on-line solution of the above problem. Basically, this algorithm utilizes the orthogonality property of the residual time series to force the filter to automatically track the optimal gain levels in a changing environment.     

Design and Application of an Adaptive Tracking Filter Control System

The design of an adaptive tracking filter control system and its application to large flexible booster vehicles is described. The problem of elastic vehicle stability is considered along with its solution by conventional and adaptive techniques. The improvement in vehicle stability, which may be achieved with the adaptive tracking filter technique as compared to conventional techniques, is shown. The control system evolved uses two adaptive tracking filters to phase stabilize the first and second bending modes, in addition to conventional compensation techniques. The application of this adaptive technique to a vehicle in which the modal frequencies are in close proximity (<2.5 percent separation) is discussed. The mechanization of the adaptive control system involves the selection of design techniques and components that are electrically and physically compatible with the intended airborne application. The development of a suitable frequency tracking technique and tracking filter is described, in addition to the electronic and mechanical design of the adaptive control system prototype.