Efficient solution and performance analysis of 3-D positionestimation by trilateration

A new exact, explicit, and computationally efficient solution for three-dimensional (3-D) position estimation based on range measurements from three stations is proposed. The simple polynomial-type form of the new algorithm facilitates the performance analysis. Formulae are provided for both the variance and the bias of the position estimates. The systematic error is a joint effect of both the measurement noise and the system nonlinearity and its magnitude cannot be ignored if highly accurate localization is required. Performance evaluation results are presented for various conditions     

固体火箭发动机不稳定燃烧研究进展

对固体火箭发动机不稳定燃烧的国内外研究现状和进展进行了详细综述.分别从物理概念、理论预估模型、实验研究、数值模拟等方面出发,论述了不稳定燃烧研究过程中的难点和一些经验教训.提出了应加强流场与声场能量交换、铝粉综合作用等机理的理论研究;开展分布燃烧、脉冲触发不稳定燃烧的实验研究;进一步开发稳定性预估软件等观点,为国内固体火箭发动机在该领域的研究提供参考.      

Adaptive data fusion framework for modeling of non-uniform aerodynamic data

Multi-fidelity Data Fusion(MDF) frameworks have emerged as a prominent approach to producing economical but accurate surrogate models for aerodynamic data modeling by integrating data with different fidelity levels. However, most existing MDF frameworks assume a uniform data structure between sampling data sources; thus, producing an accurate solution at the required level, for cases of non-uniform data structures is challenging. To address this challenge, an Adaptive Multi-fidelity Data Fusion(...     

Thermospheric gravity waves: Observations and interpretation using the transfer function model (TFM)

Gravity waves are prominent in the polar region of the terrestiral thermosphere, and can be excited by perturbations in Joule heating and Lorents force due to magnetospheric processes. We show observations from the Dynamics Explorer-2 satellite to illustrate the complexity of the phenomenon and review the transfer function model (TFM) which has guided our interpretation. On a statistical basis, the observed atmospheric perturbations decrease from the poles toward the equator and tend to correlate with the magnetic activity index, Ap, although individual measurements indicate that the magnetic index is often a poor measure of gravity wave excitation. The theoretical models devised to describe gravity waves are multifaceted. On one end are fully analytical, linear models which are based on the work of Hines. On the other end are fully numerical, thermospheric general circulation models (TGCMs) which incorporate non-linear processes and wave mean flow interactions. The transfer function model (TFM) discussed in this paper is between these two approaches. It is less restrictive than the analytical approach and relates the global propagation of gravity waves to their excitation. Compared with TGCMs, the TFM is simplified by its linear approximation; but it is not limited in spatial and temporal resolution, and the TFM describes the wave propagation through the lower atmosphere. Moreover, the TFM is semianalytical which helps in delineating the wave components. Using expansions in terms of spherical harmonics and Fourier components, the transfer function is obtained from numerical height integration. This is time consuming computationally but needs to be done only once. Once such a transfer function is computed, the wave response to arbitrary source distributions on the globe can then be constructed in very short order. In this review, we discuss some numerical experiments performed with the TFM, to study the various wave components excited in the auroral regions which propagate through the thermosphere and lower atmosphere, and to elucidate the properties of realistic source geometries. The model is applied to the interpretation of satellite measurements. Gravity waves observed in the thermosphere of Venus are also discussed.     

Fast Algorithms for Time Domain Broadband Adaptive Array Processing

Recursive algorithms are presented for time domain, broadband, adaptive beamforming. The algorithms are rapidly converging and can be computationally efficient for a certain range of array processor parameters. The algorithms are presented for two forms of array processor. One form is a Frost-type structure in which explicit constraints are required for defining the array-look direction and also to control the sensitivity of the array processor to implementation errors. The other form is a partitioned array processor in which constraints are built into the processor and the adaptive weight control algorithm is therefore unconstrained. The two processors presented are both element-space processors but the algorithms can be applied also to beam-space processors.     

Scatter factor confidence interval estimate of least square maximum entropy quantile function for small samples

Classic maximum entropy quantile function method (CMEQFM) based on the probabil-ity weighted moments (PWMs) can accurately estimate the quantile function of random variable on small samples, but inaccurately on the very small samples. To overcome this weakness, least square maximum entropy quantile function method (LSMEQFM) and that with constraint condition (LSMEQFMCC) are proposed. To improve the confidence level of quantile function estimation, scatter factor method is combined with maximum entropy method to estimate the confidence inter-val of quantile function. From the comparisons of these methods about two common probability distributions and one engineering application, it is showed that CMEQFM can estimate the quan-tile function accurately on the small samples but inaccurately on the very small samples (10 sam-ples); LSMEQFM and LSMEQFMCC can be successfully applied to the very small samples;with consideration of the constraint condition on quantile function, LSMEQFMCC is more stable and computationally accurate than LSMEQFM; scatter factor confidence interval estimation method based on LSMEQFM or LSMEQFMCC has good estimation accuracy on the confidence interval of quantile function, and that based on LSMEQFMCC is the most stable and accurate method on the very small samples (10 samples).     

Kinetic Characterization of Plasma Sheet Dynamics

The Wind spacecraft made 26 perigee passes through the near-earth plasma sheet region during 1994 to 1997. Nearly all of these passes obtained plasma data from substorms and bursty bulk flow (BBF) events. New features of ion distributions have been observed in both the plasma sheet boundary layer (PSBL) and the central plasma sheet (CPS) in the vicinity of the current sheet that are relevant for understanding the structure of the PSBL and the mechanisms of particle acceleration to MeV energies associated with the BBF events. Kinetic processes are key to understanding these new observations that are not adequately explained by existing magnetohydrodynamics (MHD) models and theories. This article will feature the phase space distribution functions as the primary data product. The main purpose of this article is to establish an observational framework for new improved models and theories. The new observations should challenge modelers and theorists.     

The future of space plasma simulation

Space plasma simulation is a subject which is in its infancy, but which is already having an important impact on space science. Its growth is being spurred onward by the continuing increase in capacity (speed and memory) of computers and by advances in the sophistication of numerical models. These advances are making it possible to simulate more realistic situations using more complex models. Already significant three-dimensional MHD calculations of the magnetosphere and its interaction with the solar wind have been carried out. In addition multi-dimensional particle simulations are illuminating many of the microscopic physics processes which go on (instabilities, saturation levels and wave nonlinearity, shock structure, etc.). Notwithstanding these advances, the surface has only been scratched; many challenges and opportunities are provided by simulation both for the space physicist and the model builders (also for computer designers). In MHD models more physics need to be included (Hall effect, gyroviscosity, accurate models of boundaries, how do we put microscopic physics effects into macroscopic codes, etc.). For model builders correct treatments of systems containing a large range of important space and time scales, magnetic field strengths, Alfven wave velocity, etc. present real challenges. What are the best ways to diagnose these complex models and obtain meaningful information? What quantities should be looked at? How should they be displayed? A discussion of the promises, the prospects, and the challenges of the above topics will be given with examples taken from recent work.     

l1-based calibration of POD-Galerkin models of two-dimensional unsteady flows

This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system. Herein, the generation of an accurate reduced order model of two-dimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques. The cornerstone of the approach is l₁ regularised regression, resulting in sparsely-connected models where only the important quadratic interactions between modes are retained. The original dynamical behaviour is reproduced at low computational costs, as few quadratic interactions need to be evaluated. The approach has two key features. First, interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required. Second, the presence of a regularisation term improves the predictive performance of the original model, generally affected by noise and poor data quality. Test cases are for two-dimensional lid-driven cavity flows, at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum. It is found that: (A) the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients; this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible; (B) sparse models maintain a good temporal stability for predictions. The methodology is ready for more complex applications without modifications of the underlying theory, and the integration into a cyber-physical model is feasible.     

考虑不确定性的飞机总体参数优化方法

由于在各种设计问题包括飞机概念设计中都存在一定的不确定性,因此在总体参数优化时有必要考虑这种不确定性。以大型客机总体参数优化设计为例,定义了考虑不确定性的飞机总体参数优化问题,该问题与传统飞机总体参数优化的区别是要进行不确定性分析。而不确定性分析的计算量过大,为此提出了一种渐进代理模型方法来解决这一难题。在建立代理模型时,通过连续成批地在设计空间的全局和局部均加入新样本点,不断提高代理模型的全局拟合精度,直至获得满意的代理模型为止。然后在优化过程中使用计算量小的代理模型。大型客机总体参数优化问题中含有5个设计变量,目标函数为起飞重量最轻,并需满足4个性能约束。考虑了不确定性后,不仅使目标值（起飞重量）对总体参数变化的敏感度有所减小,而且满足约束（设计要求）概率显著提高。     

Gravity modeling in aerospace applications

The science of inertial navigation has evolved to the point that the traditional gravity model is a principal error source in advanced, precise systems. Specifically, the unmodeled vertical deflections of the earth's gravitational field are a major contributor to CEP (circular error probable) divergence in precise terrestrial inertial navigation systems (INS). Over the years, several studies have been undertaken to the development of advanced techniques for accurate, real-time compensation of gravity disturbance vectors. More complex on-board gravity models which compute vertical deflection components will reduce the CEP divergence rate, but imperfect modeling due to on-board processing limitations will still cause residual vertical deflection errors. In order to eliminate or reduce gravity-induced errors in the INS requires measurement of gravity disturbance values and in-flight compensation to the inertial navigator. It is assumed in this paper that gravity disturbance values have been measured prior to the airborne mission and various techniques for compensation are to be considered. As part of a screening process in this study, several gravity compensation techniques (both deterministic and stochastic models) were investigated. The screening process involved identification of gravity models and algorithms, and developments of selection criteria for subsequent screening of the candidates.     

Multi-EAP:Extended EAP for multi-estimate extraction for SMC-PHD filter

The ability to extract state-estimates for each target of a multi-target posterior, referred to as multi-estimate extraction (MEE), is an essential requirement for a multi-target filter, whose key performance assessments are based on accuracy, computational efficiency and reliability. The probability hypothesis density (PHD) filter, implemented by the sequential Monte Carlo approach, affords a computationally efficient solution to general multi-target filtering for a time-varying num-ber of targets, but leaves no clue for optimal MEE. In this paper, new data association techniques are proposed to distinguish real measurements of targets from clutter, as well as to associate par-ticles with measurements. The MEE problem is then formulated as a family of parallel single-estimate extraction problems, facilitating the use of the classic expected a posteriori (EAP) estima-tor, namely the multi-EAP (MEAP) estimator. The resulting MEAP estimator is free of iterative clustering computation, computes quickly and yields accurate and reliable estimates. Typical sim-ulation scenarios are employed to demonstrate the superiority of the MEAP estimator over existing methods in terms of faster processing speed and better estimation accuracy.     

Tracking a 3D maneuvering target with passive sensors

A novel application of the interacting multiple models (IMM) algorithm in which passive infrared sensors are fused for tracking a target maneuvering in three dimensions is discussed. More accurate models of target motion are proposed to improve performance. When the general models are used to describe the maneuvering periods, it is shown that the IMM behaviour is not satisfactory, in that the innovations associated with the different models do not discriminate between the corresponding target maneuvering regimes. The turning of the Markov chain transition matrix, i.e., a priori information, is then crucial to obtaining the correct ordering of the a posteriori regime probabilities. On the contrary, a more satisfactory behavior of the IMM algorithm is obtained by carefully selecting the target motion models in the different regimes     

Review of the CIV phenomenon

Alfvén's Critical Ionization Velocity (CIV) phenomenon is reviewed, with the main emphasis on comparisons between experimental and theoretical results. The review covers (1) the velocity measurements in laboratory experiments, (2) the effect of wall interaction, (3) the experimental and theoretical limits to the magnetic field strength and the neutral density, (4) ionospheric release experiments, (5) theoretical models for electron energization in comparison to experimental results, and (6) CIV models. All laboratory investigations of the CIV are found to obey the three following simple rules of thumb: (1) if the magnetic field is so strong that V _A > 3V ₀, and if there is enough neutral gas that the Townsend condition is fulfilled, then the CIV effect occurs, (2) when it occurs, the threshold velocity (or E/B value) is within ± 50% of Alfvén's proposed value V _c , and (3) for weaker magnetic fields, the effect gradually becomes irreproducible or weak and disappears altogether for V _A < V ₀. The theoretical understanding of the process has grown rapidly during the last decade, mainly due to the introduction of computer simulation models which have to a large degree confirmed and extended earlier analytical theories. The CIV mechanism is not due to one single plasma process, but to several different mechanisms which are applicable in different parameter regimes and geometries. The computer simulations have shown that in order to understand the mechanism properly it is necessary to consider a large number of interlocking collisional and plasma processes. The theoretical development has reached the stage where it should be possible to adapt computer simulation models to specific experiments and predict ionization rates, plasma flow velocities, E/B values, particle distributions, and wave spectra. Such models should for the first time provide a really firm basis for extrapolations of the CIV process to space applications.     

Multitarget tracking using the joint multitarget probability density

This work addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD). Estimation of the JMPD is done in a Bayesian framework and provides a method for tracking multiple targets which allows nonlinear target motion and measurement to state coupling as well as nonGaussian target state densities. The JMPD technique simultaneously estimates both the target states and the number of targets in the surveillance region based on the set of measurements made. We give an implementation of the JMPD method based on particle filtering techniques and provide an adaptive sampling scheme which explicitly models the multitarget nature of the problem. We show that this implementation of the JMPD technique provides a natural way to track a collection of targets, is computationally tractable, and performs well under difficult conditions such as target crossing, convoy movement, and low measurement signal-to-noise ratio (SNR).     

月球重力场模型误差对CE-5T1探测器定轨的影响

利用嫦娥五号再入返回飞行试验拓展任务期间获取的探测器(CE-5T1)实测数据,采用内符合方法比较了3种重力场模型的实测数据定轨结果,发现采用GRAIL(Gravity Recovery And Interior Laboratory,重力恢复与内部实验室)重力场模型进行定轨的结果最优。相比于之前的嫦娥系列探测器定轨常用的LP(Lunar Prospector,月球勘探者)重力场模型,采用GRAIL重力场模型定轨后测距数据的残差降低了1个量级。进一步采用不同重力场模型进行轨道外推,定量分析重力场模型对不同类型轨道的影响,结果表明,对于倾角为90°的环月极轨道,不同重力场模型的轨道外推结果差异较小;而对于倾角为20°和40°的环月轨道,不同重力场模型的外推星历的偏差均方根可达到2km,大于当前环月探测器的定轨精度。为此,建议在后续探月任务中使用GRAIL重力场模型进行轨道确定。     

Algorithms for Fast Image Registration

The automatic determination of local similarity between two images (image registration) is one of the most fundamental problems of image processing and pattern recognition. A class of registration algorithms that are reasonably efficient and robust for translational displacement has been considered to determine relative shift between reference and search images. Stochastic image models defined on a rectangular region of support are used to determine feature vectors associated with reference and search images. A new measure, namely, coefficient of variation, is defined to take into account effects of contrast and sharpness of the images. Based upon this measure, a computationally efficient two-stage algorithm is obtained by combining the image-model based algorithm with a template matching technique. Simulation results with several synthetic and real images are presented to evaluate the performance of the algorithms.     

Instantaneous Frequency Estimation Using Adaptive Linear Predictor Weights

A computationally efficient scheme for estimating the digital instantaneous frequencies of narrowband inputs is introduced. The frequency estimates are obtained by searching for minima of the inverse input power spectrum. This spectrum is estimated at each input sample from the weights of an adaptive linear predictor which uses the LMS (least mean square) algorithm to update its weights. The related minima are sought via an iterative search algorithm, referred to as the iterative frequency estimator. This algorithm is computationally more efficient than available methods, and also provides a higher resolution. Simulation results are included; these include tracking of random message sequences in FM signals, and the formant frequency estimation of speech.     

Analysis of pressure characteristics under laminar and turbulent flow states inside the pilot stage of a deflection flapper servo-valve: Mathematical modeling with CFD study and experimental validation

Electro-hydraulic servo-valves are widely used components in the mechanical industry, aerospace and aerodynamic devices which precisely control the airplane or missile wings. Due to the small size and complex structure in the pilot stage of deflection flapper servo-valves, accurate mathematical models for the flow and pressure characteristics have always been very difficult to be built. In this paper, mathematical models for the pilot stage of deflection flapper servo-valve are investigated to overcome some gaps between the theoretical formulation and overall performance of the valve by considering different flow states. Here, a mathematical model of the velocity distribution at the flapper groove exit is established by using Schlichting velocity equations for in-compressible laminar fluid flow. Moreover, when the flow becomes turbulent, a mathematical model of pressure characteristics in the receiving ports is built on the basis of the assumption of the collision between the liquid and the jet as the impact of the jet on a moving block of fluid particles. To verify the analytical models for both laminar and turbulent flows, the pressure characteristics of the deflection flapper pilot stage are calculated and tested by using numerical simulation and experiment. Experimental verification of the theory is also presented. The computed numerical and analytical results show a good agreement with experimental data.     

基于遗传算法与响应面模型的压气机叶片气动优化设计

1引言由于叶轮机械内部复杂的三维流动,各种波涡结构的广泛存在,吸引了众多学者对其进行了积极的探索与研究。CFD作为可靠省时的设计手段之一,在叶轮机械气动设计的过程中显示了其卓越的性能[1~3]。June Chung和Lee K i D[4]采用基于梯度法的优化程序,以绝热效率为目标函数对NA