改进的极大似然算法及其在试飞数据处理中的应用

通过对一般极大似然辨识算法的分析,提出一种改进的极大似然辨识方法,使之更适合于飞机飞行试验数据处理。将其应用于纵横向耦合的六自由度飞机的飞行试验数据的协调性检验及重建。结果表明：这种方法使参数辨识的收敛速度得到大大提高,使参数初值更易于选择。     

Theory of angle estimation using a multiarm spiral antenna

An analysis of angle estimation using a single aperture, multimode spiral is presented. It is demonstrated that in addition to the classical Comparison method, modern parameter estimation techniques such as Multiple Signal Classification (MUSIC) and MLM (Maximum Likelihood Method) can be applied to multimode antenna technology for angle estimation. These techniques, coupled with the advent of digital receivers make possible the elimination of the mode-forming network. Results of computer simulations show that these new approaches give lower bias and variance, and also extend coverage toward boresight compared with the traditional Comparison method     

一种实时飞行轨迹重构方法

提出一种有效的实时纵向飞行轨迹重构的新方法。为了得到状态估计的快速算法,本文把非线性飞行轨迹重构转化为线性、离散、时变状态和参数估计问题。将数值稳定性好、计算量也小的序列U-D分解滤波算法用于状态方程为线性、观测方程为线性或非线性的滤波问题中。由于测量值中常常含有系统偏差,本文把这些偏差作为增广状态加入增广状态模型中,并利用模型的一些特点,提出偏差分离的U-D分解算法,使计算量大大减少。仿真和实际试飞数据计算表明、本文的方法可得到比平方根协方差滤波更有效的实时飞行轨迹重构结果。     

无人机动态RCS测量及数据统计分析

以某无人机的动态RCS特性作为研究对象,设计了无人机的测试飞行航路,应用非线性最小二乘估计方法,对采集到的无人机动态RCS试验数据进行X^2分布和对数正态分布模型的参数估计,降低了测量噪声对统计模型参数估计的影响,较为理想地解决了数学统计模型参数估计中试验数据测量噪声的影响,并对某无人机的动态RCS统计分布特点做了分析。     

Fault diagnosis based on measurement reconstruction of HPT exit pressure for turbofan engine

Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.     

利用大迎角试飞数据辨识飞机气动导数

基于用局部线化代替非线性概念．探索了利用大迎角飞行试验数据辨识飞机空气动力参数问题。在准定常假设条件下，提出了迎角分割算法和时间分割算法，针对歼教七飞机的失速飞行试验数据，用最小二乘回归方法和最大似然法验证了上述大迎角参数辨识的思想，取得了较好的结果，为进一步开展大迎角参数辨识技术的工程应用奠定了基础。     

非线性滤波方法及其在飞行状态及参数估计中的应用

基于非线性系统高阶近似的思想,提出一种比推广卡尔曼滤波（ＥＫＦ）更接近非线性系统本质的近似滤波方法,并应用于飞行状态的参数估计（或称为飞行轨迹重构）问题。仿真和实际飞行数据计算结果表明：提出的非线性近似滤波方法比ＥＫＦ有更高的估计精度和更好的鲁棒性,对飞机机动形状、数据长度要求不高,滤波收敛速度快。利用飞行状态估计数学模型的具体特点,使计算量和存储量大幅度减少。该方法应用于非线性较强的飞行状态及参数估计问题。可得到比ＥＫＦ更好的结果。     

一种基于云模型优化的飞行器参数辨识算法

极大似然估计方法(ML)在飞行器参数辨识中得到了广泛应用,该方法需要预先推导灵敏度方程,进而求解灵敏度矩阵,在应用过程中比较繁杂,且容易陷入局部最优。提出一种基于云模型优化的飞行器参数辨识算法,根据极大似然估计原理,利用云模型的优化理论对极大似然函数进行优化,从而得到待辨识参数值。该算法不必推导灵敏度矩阵,对初值要求不高,应用便捷,且保留了云模型优化的特点,收敛速度较快、不易陷入局部最优。以Twin Otter飞机为例对算法进行验证。结果表明:算法易于实现、辨识结果精度较高、收敛速度较快,不易陷入局部最优。     

自适应卡尔曼滤波在航空发动机参数估计中的应用

介绍根据实际飞行数据并用卡尔曼滤波方法对某型发动机的参数估计及其结果。重点研究了卡尔曼滤波在航空发动机参数估计中的滤波发散问题和解决这一问题的自适应卡尔曼滤波、飞行条件补偿及模型修正的综合方法。      

非线性分离算法及其在飞行试验中的应用

 本文根据最小方差估计和分离算法原理,提出一种新的非线性状态估计和偏差辨识的分离算法。并用此算法确定飞行状态和测试仪器的误差,同时U-D分解保证计算效率和数值稳定性。为了得到数据相容性检验的准确结果,本文采用直接离散化的飞机运动模型,以减小模型误差。通过仿真并在我国两种歼击机上实际应用,结果表明本文所给的算法对不同的初值和噪声统计特性都能得到飞行数据相容性检验的一致结果,并能用于低采样率下的数据相容性检验。     

振动系统参数识别的三个新方法

近年来,振动系统参数识别技术受到了越来越多的重视。振动系统参数识别的谱分析方法（频域方法）发展得比较成熟。但它也有一些缺点,其中之一是需要了解激振力。     

A systematic approach to nonlinear rotorcraft model identification

The development of a powerful parameter estimation routine and its integration into the simulation environment HOST is described. With this tool approaches are being made towards new strategies of mathematical modeling, aimed at providing highly accurate and nevertheless run-time efficient simulation models. The identification routine is capable of optimizing parameterized models in both dynamic time domain simulation and static (e.g. trim state variation) conditions. Examples of both cases are presented to emphasize the improvement in the system response prediction and to demonstrate the abilities of the identification techniques in combination with the nonlinear simulation platform. This article reviews the activities and achievements accomplished by the DLR Institute of Flight Research and the ONERA Systems Control and Flight Dynamics Department during the last few years in the research on rotorcraft flight dynamics modeling and model identification. Future activities that require extensive high fidelity modeling are in the scope of the current and coming modeling activities that include the use of the presented methods and software technologies.     

基于Viterbi算法的扩频码与信息序列联合估计

针对短码DSSS（Direct Sequence Spread Spectrum,直接序列扩频）信号扩频码MLE（Maximum Likelihood Estimation,最大似然估计）问题,提出了一种基于Viterbi算法的扩频码搜索方法,并将其应用到同步CDMA（Code Division Multiple Access,码分多址）信号的扩频码估计中.该算法利用了扩频码码元为±1的先验知识,以向量的2-范数平方或1-范数作为度量值;每次判决扩频码码元时,计算2条可能路径的度量值,并选择使度量值最大的那条路径作为幸存路径,最终的幸存路径即为估计的扩频码;所提算法不仅计算复杂度低,而且能同时估计扩频信号的扩频码和信息序列.仿真实验表明,本算法在低信噪比时同样具有较好的性能.     

Unsteady aerodynamic modeling at high angles of attack using support vector machines

Accurate aerodynamic models are the basis of flight simulation and control law design.Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determination and parameter estimation due to little understanding of the flow mechanism.Support vector machines(SVMs)based on statistical learning theory provide a novel tool for nonlinear system modeling.The work presented here examines the feasibility of applying SVMs to high angle-of-attack unsteady aerodynamic modeling field.Mainly,after a review of SVMs,several issues associated with unsteady aerodynamic modeling by use of SVMs are discussed in detail,such as selection of input variables,selection of output variables and determination of SVM parameters.The least squares SVM(LS-SVM)models are set up from certain dynamic wind tunnel test data of a delta wing and an aircraft configuration,and then used to predict the aerodynamic responses in other tests.The predictions are in good agreement with the test data,which indicates the satisfying learning and generalization performance of LS-SVMs.     

一种基于多普勒频率的恒模信号直接定位方法

相比于传统的差分多普勒(DD)两步定位方法,以Amar和Weiss提出的基于多普勒频率的单步直接定位方法在低信噪比和小样本条件下具有更高的定位精度。在该类新型定位体制的基础上,提出了一种基于多普勒频率的恒模信号直接定位方法。首先,依据最大似然(ML)准则以及恒模信号的恒包络特征,建立相应的直接定位优化模型。然后,根据目标函数的代数特征将全部未知参量分成两组,并提出一种有效的多参量交替迭代算法,用以获得该优化问题的最优数值解。新算法包含了针对这两组未知参量的Newton型迭代公式,用以避免网格搜索,并能实现多维参数的"解耦合"估计。最后,推导出针对恒模信号的目标位置直接估计方差的克拉美罗界(CRB)。数值实验验证了新方法的优越性。     

Digital Control of High Performance Aircraft Using Adaptive Estimation Techniques

Since the early 1960's, a rapid advance in signal processing, including filtering and estimation techniques, has been evident. In contrast, applied feedback control, particularly for aircraft, is currently based on technology available prior to 1960, i. e., primarily either constant gain feedback or at most a standard gain-scheduling. In this paper, an adaptive signal processing algorithm is joined with gain-scheduling to produce an effective scheme for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance short-takeoff-and-landing (STOL) aircraft. The actual controller views the nonlinear behavior of the aircraft as being equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. From the analysis of the reduced-order model the nonlinear behavior has been found to be well approximated by assuming an effective switching of the linear models at random times, the durations of which reflect the motion of the aircraft in response to pilot commands.     

直升机单发失效后自转着陆轨迹优化

建立了直升机单发失效后增广的纵向三维刚体飞行动力学模型,通过选择合适的目标函数、路径约束和边界约束,将自转着陆问题表示成非线性最优控制问题,使用非线性规划方法求解得到自转着陆的最优轨迹和操纵.以UH-60直升机为例,首先计算了自转着陆距离最短的最优解,并与二维点质量模型进行对比.结果表明三维刚体模型在旋翼转速、旋翼拉力...     

Wideband channel model for aeronautical telemetry

A multipath channel model for wideband aeronautical telemetry links is presented. Channel sounding data were collected at Edwards AFB, CA, at both L-band and lower S-band. Frequency domain analysis techniques were used to evaluate candidate channel models. The channel model is composed of three propagation paths: a line-of-sight direct path and two specular reflections. The first specular reflection is characterized by a relative amplitude of 70% to 96% of the line-of-sight amplitude and a delay of 10-80 ns. This path is the result of "ground bounces" off the dry lake bed at Edwards and is a typical terrain feature at DoD test ranges located in the western United States. The amplitude and delay of this path are defined completely by the flight path geometry. The second path has much lower amplitude and a longer delay. The gain of this path is well modeled as a zero-mean complex Gaussian random variable. The relative amplitude is approximately 2% to 8% of the line-of-sight amplitude. The mean excess delay is 155 ns with an rms delay spread of 74 ns.     

Adaptive model architecture and extended Kalman-Bucy filters

In radar systems, extended Kalman-Bucy filters (EKBFs) are used to estimate state vectors of objects in track. Filter models accounting for fundamental aerodynamic forces on reentry vehicles are well known. A general model structure accommodating the dynamics of reentry vehicles in both exoatmospheric and endoatmospheric flight is presented. The associated EKBFs for these various models are described and the resulting associated parameter estimation and identification problems are discussed. The effects of position, velocity, drag, and aerodynamic lift are described within a nested set of EKBF models     

一种飞行器投放分离气动力辨识修正方法

空中投放发射的大翼面飞行器的分离轨迹与姿态受载机干扰流场影响更加明显,对分离时干扰气动数据库的准确性提出了更高要求。针对投放分离干扰气动力特点,提出了一种简化的差量气动力模型,并给出了一套飞行数据处理与参数预估计的方法。分离段飞行数据的辨识结果与六自由度飞行动力学仿真结果说明了提出的差量气动模型与相关数据处理方法的有效性。用辨识结果对气动数据库进行修正提高了数据库的准确度,可提高分离安全飞行仿真分析的精度。