Improving GPS-Based Landing System Performance using an Empirical Barometric Altimeter Confidence Bound

This paper develops an empirical confidence bound for barometric altimeter altitude errors and shows how this bound may improve the performance of GPS-based approach and landing systems. This empirical bound is developed using historical meteorological data collected at a set of geographically diverse locations over a thirty year period. The confidence bound developed is shown to provide a Gaussian overbound on altimeter altitude errors in standard atmospheric conditions between a 10-5 and 10-6 confidence level. This confidence bound is integrated into the standard methodology for analyzing the performance of GPS-based landing systems and the results of a performance trade study using the confidence bound are presented. The results show that incorporating the empirical barometric altimeter confidence bound provides an increase in the coterminous United States (CONUS) service volume for lateral precision with vertical guidance (LPV) type approaches. While this increase is approximately 2% for an L1 single-frequency GPS user, it jumps to roughly 40% for an L5 single-frequency user.     

凸约束非凸二次规划问题的分枝定界方法

针对凸约束非凸二次规划问题,给出了一个分枝定界方法。首先,我们构造一个多胞体包含可行域,然后根据凸集上非凸二次规划问题的整体最优解在可行域边界达到的性质,对锥所包含的可行域的边界构造一个包含它的超矩形体,并对这个超矩形体构造一个外接球。我们通过求解球约束非凸二次规划问题的整体最优解来确定下界,并把锥的棱与可行域的边界交点的目标函数值的最小值作为上界,把锥剖分技术与外逼近方法结合起来寻找原问题的整体最优解。最后,我们对这个方法进行收敛性分析。     

Performance measure for Markovian switching systems using best-fitting Gaussian distributions

This paper considers the theoretical posterior Cramer-Rao lower bound (PCRLB) for the case of tracking a manoeuvring target with Markovian switching dynamics. In a recent article [2] it was proposed to calculate the PCRLB conditional on the manoeuvre sequence and then determine the bound as a weighted average, giving an unconditional PCRLB. However, we demonstrate that this approach can produce an overly optimistic lower bound, because the sequence of manoeuvres is implicitly assumed known. Motivated by this, we develop a general approach and derive a closed-form estimate of the PCRLB in the case of Markovian switching systems. The basis of the approach is to, at each time step, replace the multi-modal prior target probability density function (pdf) with a best-fitting Gaussian (BFG) approximation. We present a recursive formula for calculating the mean and covariance of this Gaussian distribution, and demonstrate how the covariance increases as a result of the potential manoeuvres. We are then able to calculate the PCRLB for this BFG model using an existing Riccati-like recursion. Because of the BFG approximation, we are no longer guaranteed a bound and so we refer to our estimate as an "error performance measure" rather than a bound. The presented approach is applied both to filtering and smoothing cases. The simulation results indicate a very close agreement between the proposed performance measure and the error performance of an interacting multiple model estimator.     

An application of embedology to spatio-temporal pattern recognition

The theory of embedded time series is shown applicable for determining a reasonable lower bound on the length of test sequence required for accurate classification of moving objects. Sequentially recorded feature vectors of a moving object form a training trajectory in feature space. Each of the sequences of feature vector components is a time series, and under certain conditions, each of these time series has approximately the same fractal dimension. The embedding theorem may be applied to this fractal dimension to establish a sufficient number of observations to determine the feature space trajectory of the object. It is argued that this number is a reasonable lower bound on test sequence length for use in object classification. Experiments with data corresponding to five military vehicles (observed following a projected Lorenz trajectory on a viewing sphere) show that this bound is indeed adequate     

On Computing the Cramer-Rao Bound for a Random Signal

The Cramer-Rao bound for estimating parameters of a random signal is obtained using a sampled data approach. A numerical example is presented to illustrate the result. In two limiting cases, it is shown that this bound converges to the well-known bounds for the point and Rayleigh targets.     

Comments on "on Probability of Error in Decision Feedback Equalizer"

The above-mentioned paper [1] derives bounds on the error probability of a decision feedback equalizer (DFE) which are claimed to be significantly tighter than the earlier upper bound of [2]. Unfortunately, [1] makes an unsupportable assumption which reddars the conclusions incorrect. We show that valid bounds can be obtained by the methods of [1], but that for the numerical example of [2] , the resulting upper bound is never tighter than, and sometimes significantly weaker than, that derived in [2]. Similarly, a lower bound derived by the method of [1] is shown for the same numerical example to be very close to the error-free past lower bound previously known.     

Trajectory Estimation with Uncertain and Nonassociated Data

The local behavior of a maximum likelihood estimator that adaptively weights data of uncertain origin to make a probabilistic measurement-to-track assignment is examined. The results are placed in the framework of the classic estimation theory of Fisher and Cramer. The Cramer-Rao bound is derived and the MLS error level is compared with this lower bound and the level achieved with known data association. Deterioration in performance was found to depend solely on the false-detection to valid-contact ratio, and the actual (measured) covariance matrix is a scalar multiple of the covariance matrix computed for associated data.     

Generalized Kutta–Joukowski theorem for multi-vortex and multi-airfoil flow with vortex production——A general model

By using a special momentum approach and with the help of interchange between singularity velocity and induced flow velocity, we derive in a physical way explicit force formulas for twodimensional inviscid flow involving multiple bound and free vortices, multiple airfoils, and vortex production. These force formulas hold individually for each airfoil thus allowing for force decomposition, and the contributions to forces from singularities(such as bound and image vortices,sources, and doublets) and bodies out of an airfoil are related to their induced velocities at the locations of singularities inside this airfoil. The force contribution due to vortex production is related to the vortex production rate and the distance between each pair of vortices in production, thus frameindependent. The formulas are validated against a number of standard problems. These force formulas, which generalize the classic Kutta–Joukowski theorem(for a single bound vortex) and the recent generalized Lagally theorem(for problems without a bound vortex and vortex production) to more general cases, can be used to identify or understand the roles of outside vortices and bodies on the forces of the actual body, optimize arrangement of outside vortices and bodies for force enhancement or reduction, and derive analytical force formulas once the flow field is given or known.     

三阶段疲劳全寿命估算模型

 本文给出了小裂纹范围的完整定义,并根据此定义提出了“三阶段疲劳全寿命估算模型”,即全寿命由裂纹形成寿命、小裂纹扩展寿命和大裂纹扩展寿命所组成。用此模型估算得到的寿命与实验结果符合很好。     

弹道中段目标进动周期估计的改进自相关法

自相关法可用于估计弹道中段雷达目标的进动周期,它需要预先给出进动周期的上下限。进动周期下限可能远小于真实进动周期,此时自相关法的估计性能将严重下降。定义了自相关函数(ACF)的凸包,在此基础上提出了一种改进的自相关法。首先求出ACF和其凸包的差函数,然后搜索差函数的最大值,从而得到进动周期的估计值。理论分析和仿真结果表明:当进动周期下限和真实进动周期相差不大时,该方法的估计性能接近自相关法;当进动周期下限远小于真实进动周期时,该方法仍然具有良好的估计性能;由于进动周期的上下限之比通常大于2,因此该方法的计算量比自相关法增大的倍数小于1.4;同时它对先验信息的要求非常宽松。因此该方法具有广泛的适用性。     

变薄拉深的上限法分析

根据上限法原理建立了一种适用于分析变薄拉深的上限模型,包括两个用于优化上限解的独立参数。通过优化计算,变薄拉深力理论值与实验值吻合良好;用该模型研究了变薄拉深系数、凹模半锥角、原始筒形件内外径比、定径带相对长度以及内外摩擦因子等主要工艺参数对变薄拉深力的影响规律。     

Bounds on Elevation Error Estimates of a Target in Multipath

The Cramer-Rao bound for an unbiased estimate of the elevation angle of a target in the presence of multipath is calculated for the symmetric (target and image symmetric about the elevation symmetry plane of antenna) and nonsymmetric cases for an antenna consisting of 21 elements. These bounds are compared to the maximum likelihood estimates and it is found that the rms error of the maximum likelihood estimate (which has a bias) is below the Cramer-Rao bound for unbiased estimates.     

Degradation of Signal-to-Noise Ratio Due to IF Filtering

A receiver for biphase modulated signals using an integrate-and-dump filter is optimum only if the IF filter bandwidth is infinite. Finite IF filter bandwidth results is a performance degradation. Using the predetection signal-to-noise ratio as the performance criterion, a lower bound on this quantity is determined as a function of the ratio (IF filter bandwidth)/(bit rate). The corresponding upper bound on the error probability is also presented.     

The exact Cramer-Rao bound for Gaussian autoregressive processes

An explicit expression is derived for the Cramer-Rao bound (CRB) on unbiased estimates of the parameters of autoregressive (AR) processes, given a finite number of measurements. The expression converges to the well-known asymptotic form of the CRB when the number of measurements tends to infinity. The behavior of the bound is illustrated by some numerical examples     

终端区域理想速度剖面的生成

本文着重探讨了飞机进入终端区域后理想速度剖面的生成问题,目的是通过执行理想剖面生成算法,达到对飞机进行精确的时间控制,消除等待时间,提高机场利用率,达到节省燃料减少延误的目的。     

RFNN control for PMLSM drive via backstepping technique

A robust fuzzy neural network (RFNN) control system is proposed in this study to control the position of the mover of a permanent magnet linear synchronous motor (PMLSM) drive system to track periodic reference trajectories. First, an ideal feedback linearization control law is designed based on the backstepping technique. Then, a fuzzy neural network (FNN) controller is designed to be the main tracking controller of the proposed RFNN control system to mimic an ideal feedback linearization control law, and a robust controller is proposed to confront the shortcoming of the FNN controller. Moreover, to relax the requirement for the bound of uncertainty term, which comprises a minimum approximation error, optimal parameter vectors and higher order terms in Taylor series, an adaptive bound estimation is investigated where a simple adaptive algorithm is utilized to estimate the bound of uncertainty. Furthermore, the simulated and experimental results due to periodic reference trajectories demonstrate that the dynamic behaviors of the proposed control systems are robust with regard to uncertainties.     

鲁棒EKF在脉冲星导航系统中的应用

针对脉冲星导航系统的滤波问题,传统的扩展卡尔曼滤波(EKF)算法存在不能克服系统模型存在不确定性参数以及乘性噪声等缺陷,提出一种鲁棒EKF算法。首先,分析了状态预测误差方程和估计误差方程,利用统计学原理,得到了状态预测方差矩阵和状态估计方差矩阵计算等式。由于系统模型存在不确定性参数,状态预测协方差矩阵和状态估计协方差矩阵无法计算;因此,利用4个重要矩阵不等式,分析并找到预测方差矩阵和状态估计方差矩阵的上界。最后,利用状态估计误差协方差矩阵上界设计状态增益矩阵,使得状态估计协方差矩阵的迹最小。将该算法对脉冲星导航系统进行仿真,仿真结果验证了所提算法的有效性。     

A Lower Bound to Rcomp for the Gaussian Channel with a Uniform Quantizing Demodulator

Consideration is given to a channel using orthogonal modulation, soft decision-uniform quantizing demodulation, and perturbed by additive white Gaussian noise. A lower bound is derived to the Rcomp of this channel. The bound explicity exhibits the dependence upon the degree of quantization and is easily computable. It also indicates that the uniform quantizing demodulation scheme is close to optimum for sufficiently fine quantization.     

The Effect of Interfering Signals on the Performance of Angle of Arrival Estimates

The performance of angle of arrival estimates using an array in the presence of interfering signals is evaluated using the Cramer-Rao bound. To do this, a model for interference is developed which presents the interference as narrowband, temporally white, but spatially correlated, noise. The bound is evaluated and it is shown to depend upon the ambiguity function of the array and spatial correlation matrix of the noise plus interference. Motivation of the model in the context of air traffic control and sonar surveillance is presented.     

圆棒热挤压过程研究

用抛物面速度场,对圆棒热挤压过程进行上限分析。经理论计算和有关试验数据比较,所求得的挤压力具有足够高的精度;并利用所建立的数学模型对挤压过程死区、最佳模角和挤压力进行了系统地研究。