Multiple radar targets estimation by exploiting induced amplitude modulation

This work deals with the problem of estimating complex amplitudes, Doppler frequencies, and directions of arrival (DOA) of multiple targets present in the same range-azimuth resolution cell of a surveillance radar. The maximum likelihood (ML) and the asymptotic (large sample size) ML (AML) estimators are derived. To reduce the computational complexity of the maximization of the nonlinear two-dimensional criterion function of the AML estimator, we propose a computationally efficient algorithm based on the RELAXation method. It allows decoupling the problem of jointly estimating the parameters of the signal components into a sequence of simpler problems, where the parameters of each component are separately and iteratively estimated. The proposed method overcomes the resolution limitation of the classical monopulse technique and resolves multiple targets exhibiting an arbitrarily small difference in azimuth as long as their Doppler frequencies differ at least by the inverse of the number of integrated pulses, provided that enough signal-to-noise ratio (SNR) per pulse is available. The performance of the proposed AML-RELAX estimator is numerically investigated through Monte Carlo simulation and Cramer-Rao lower bound (CRLB) calculation.     

Nonlinear Estimation Via Kalman Filtering

The extended Kalman-Bucy filtering algorithm is applied to the problem of estimating the system parameters of a single-channel missile attitude control system. In particular, noisy observations of body angular rate, normal acceleration, and control surface deflec tion are used in the algorithm to obtain estimates of body angular rate, angle of attack, control surface deflection, air density, and missile velocity. Computational results obtained for this problem are presented. These results are evaluated to determine the applicapility of this estimator as a part of an adaptive control scheme. In addition, a general approach to the formulation of practical nonlinear estimation problems is suggested.     

一种基于数据跳变检测的高动态环境GPS信号参数估计方法

鉴于高动态环境中 Ｇ Ｐ Ｓ信号参数估计和调制数据跳变检测所遇到的问题,采用扩展卡尔曼滤波方法（ Ｅ Ｋ Ｆ）对信号参数进行了估计,分析了通过载波辅助技术实现伪码延时估计的原理,重点研究了一种简单的数据跳变检测和估计参数修正方法。模拟结果表明这种方法在信号参数估计精度和动态跟踪性能等方面都能够满足高动态环境的要求。     

A serialized civil aircraft R&D cost estimation model considering commonality based on BP algorithm

The common design of serial civil aircraft, an important strategy of modern civil aircraft research and develop-ment, minimizes the whole life cycle cost of civil aircraft through asset reuse and resource sharing. However, the existing estimating model for the R&D cost of civil aircraft ignores the effects of common design, so the value estimated by estimating derivative models is significantly inconsistent with the actual one. To solve this problem, a novel assessment method for civil aircr...     

A Parametric Technique for Time Delay Estimation

The problem of estimating the time difference of arrival of a signal with unknown spectrum to two receivers is treated. A signal model containing both spectral and delay parameters is derived. The model parameters are computed by a two-step procedure: (1) the modified Yule-Walker equations are used to estimate the autoregressive spectrum of the source signal, and (2) a frequency domain squared error criterion is minimized to provide the delay estimate. The performance of the proposed technique is illustrated by simulation results.     

Statistical estimation of navigation errors

An algorithm for estimating navigation system accuracy without the use of so-called ground truth data is presented. The estimates are expressed in terms of system covariance matrices and relative bias vectors; if one of the systems is a dead-reckoning (DR) or inertial system, the algorithm also estimates drift rate parameters. A summary of tests with US Navy ships backs up the results of Monte Carlo testing. The algorithm should also have applications outside the field of navigation     

Control for unstable nonminimum phase uncertain dynamic vehicle

A control algorithm for control of linear uncertain systems is presented. This algorithm is applied to the control of an unstable nonminimum phase uncertain dynamic vehicle. The algorithm is based on the state and parameters observability canonical (SPOC) form and a certainty equivalence pole placement controller. The algorithm provides single controller for the problem of the uncertain dynamic vehicle that approaches the performance of a controller designed for perfectly known parameters within the whole range of the plant's parameters uncertainty. The algorithm is globally bounded input bounded output stable and needs only the knowledge of the order of the plant. The algorithm is presented and its performance is demonstrated by simulations     

Direction-of-arrival estimation using signal subspace modeling

A computationally viable algorithm for estimating the direction-of-arrival (DOA) of multiple wavefields that are incident on an array of sensors is developed. The geometry of the array is unrestricted and the incident wavefields may be generated by mixtures of incoherent and coherent emitting sources. In the approach taken, the sensor signals are modeled as a noise-contaminated linear combination of steering vectors which are functionally dependent on a set of DOA parameters. These parameters are to be chosen so that this sensor signal model is most compatible with empirically measured data (i.e., snapshot data). An iterative procedure is developed for selecting the most data compatible set of DOA parameters in both the snapshot domain and the array covariance matrix domain. Critical to the success of such iterative solution procedures is the generation of quality DOA parameters to initialize the algorithm. A sequential beamforming method for this initialization is presented. Numerical examples to illustrate the effectiveness of the proposed algorithmic approach are given     

Direct thrust control for multivariable turbofan engine based on affine linear parameter-varying approach

A novel turbofan Direct Thrust Control(DTC) architecture based on Linear ParameterVarying(LPV) approach for a two-spool turbofan engine thrust control is proposed in this paper.Instead of transforming thrust command to shaft speed command and pressure ratio command, the thrust will be directly controlled by an optimal controller with two control variables. LPV model of the engine is established for the designing of thrust estimator and controller. A robust LPV H∞filter is introduced to estimate ...     

基于过渡工作过程的航空发动机气路分析方法

为对发动机机动性能的退化程度进行估计,开展了基于过渡工作过程的气路分析研究。针对气路传感器数目较少的情况,采用序列工作点方法对大量的健康参数进行分析,在增加可用信息量的同时,降低了由多工作点方法的平均效应引入的参数估计系统误差。为解决发动机大偏差性能退化健康参数估计中的计算收敛性问题,提出了间接递归牛顿-拉夫逊法强化非支配分类差分进化算法。针对某型双轴分排涡扇发动机的气路分析结果表明：采用本文所提出的方法能够在气路传感器数目有限的条件下,利用发动机过渡态数据实现对大偏差范围内大量健康参数的高效、准确估计。     

Experimental study in adaptive tracking control

The authors describe an experimental study of adaptive pointing and tracking control for flexible spacecraft conducted on a complex ground experiment facility. The algorithm used is based on a multivariable direct model reference adaptive control law. Several experimental validation studies performed using this algorithm for vibration damping and robust regulation are extended by addressing the pointing and tracking problem. As is consistent with an adaptive control framework, the plant is assumed to be poorly known to the extent that only system level knowledge of its dynamics is available. Explicit bounds on the steady-state pointing error are derived as functions of the adaptive controller design parameters. It is shown that good tracking performance can be achieved in an experimental setting by adjusting adaptive controller design weightings according to the guidelines indicated by the analytical expressions for the error     

DOA and steering vector estimation using a partially calibratedarray

We consider the problem of estimating directions of arrival (DOAs) using an array of sensors, where some of the sensors are perfectly calibrated, while others are uncalibrated. We identify a cost function whose minimizer is a statistically consistent and efficient estimator of the unknown parameters-the DOAs and the gains and phases of the uncalibrated sensors. Next we present an iterative algorithm for finding the minimum of that cost function The proposed algorithm is guaranteed to converge. The performance of the estimation algorithm is compared with the Cramer Rao bound (CRB). The derivation of the bound is also included. It is shown that DOA accuracy can be improved by adding uncalibrated sensors to a precisely calibrated array. Moreover, the number of sources that can be resolved may be larger than the number that can be resolved by the calibrated portion of the array     

航天器相对运动估计的一种并行推广卡尔曼滤波方法

 从并行的观点出发，研究应用推广卡尔曼滤波估计航天器交会对接寻的期相对位置和速率问题。推导出交会推广卡尔曼滤波公式；提出了基于奇异值分解（ＳＶＤ）和Ｆａｄｄｅｖ算法的并行平方根算法；给出了其脉动阵列（Ｓｙｓｔｏｌｉｃ）实现结构；并对阵列所需的处理单元数目和执行一次迭代所需的时间步进行了分析，说明了其实现的优越性。为航天器相对运动估计提供了一种新的有效方法     

Azimuth/elevation direction finding using regular array geometries

The authors consider the problem of extending the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for multiple source, cochannel direction finding to the two-dimensional case (e.g., azimuth and elevation angle estimation). Two algorithms are presented, one based on the optimal (minimal variance) subspace fitting formulation of ESPRIT, and the other based on an approximation to it. The algorithms are applicable to antenna arrays composed of identical subarrays displaced in two dimensions, such as uniform rectangular phased arrays. Simulation results illustrating the relative performance of the algorithms are also presented     

Super resolution time delay estimation via MODE-WRELAX

We consider estimating time delays and amplitudes (real- or complex-valued) from the superposition of very closely spaced signals with known shapes. The well-known high resolution MODE (Method Of Direction Estimation) algorithm, which was originally proposed for angle estimation in array processing, is modified and used with our efficient time delay estimation method WRELAX (Weighted Fourier transform and RELAXation based) algorithm to deal with this problem. The proposed method is referred to as MODE-WRELAX. MODE-WRELAX provides better accuracy than MODE and higher resolution than WRELAX. Moreover, it can be used for both complex- and real-valued signals (including those with highly oscillatory correlation functions). Numerical results show that the MODE-WRELAX estimates can approach the corresponding Cramer-Rao bound. Efficient implementation of the algorithm is also discussed     

Image texture synthesis-by-analysis using moving-average models

A synthesis-by-analysis model for texture replication or simulation is presented. This model can closely replicate a given textured image or produce another image that although distinct from the original, has the same general visual characteristics and the same first and second-order gray-level statistics as the original image. The texture synthesis algorithm, proposed contains three distinct components: a moving-average (MA) filter, a filter excitation function, and a gray-level histogram. The analysis portion of the texture synthesis algorithm derives the three from a given image. The synthesis portion convolves the MA filter kernel with the excitation function, adds noise, and modifies the histogram of the result. The advantages of this texture model over others include conceptually and computationally simple and robust parameter estimation, inherent stability, parsimony in the number of parameters, and synthesis through convolution. The authors describe a procedure for deriving the correct MA kernel using a signal enhancement algorithm, demonstrate the effectiveness of the model by using it to mimic several diverse textured images, discuss its applicability to the problem of infrared background simulation, and include detailed algorithms for the implementation of the model     

飞机等效系统的在线辨识及其微机实现

引言 等效系统法是国外提出的评价带有复杂控制系统的飞机飞行品质的一种较有效的方法。它的基本思想是寻找一个带有等效时间延迟的低阶系统,使该系统具有或近似保留给定增稳飞机的高阶系统输出响应的主导特性,然后将低阶系统参数与规范要求相比     

Ballistic missile track initiation from satellite observations

An algorithm is presented to initiate tracks of a ballistic missile in the initial exoatmospheric phase, using line of sight (LOS) measurements from one or more moving platforms (typically satellites). The major feature of this problem is the poor target motion observability which results in a very ill-conditioned estimation problem. The Gauss-Newton iterative least squares minimization algorithm for estimating the state of a nonlinear deterministic system with nonlinear noisy measurements has been previously applied to the problem of angles-only orbit determination using more than three observations. A major shortcoming of this approach is that convergence of the algorithm depends strongly on the initial guess. By using the more sophisticated Levenberg-Marquardt method in place of the simpler Gauss-Newton algorithm and by developing robust new methods for obtaining the initial guess in both single and multiple satellite scenarios, the above mentioned difficulties have been overcome. In addition, an expression for the Cramer-Rao lower bound (CRLB) on the error covariance matrix of the estimate is derived. We also incorporate additional partial information as an extra pseudomeasurement and determine a modified maximum likelihood (ML) estimate of the target state and the associated bound on the covariance matrix. In most practical situations, probabilistic models of the target altitude and/or speed at the initial point constitute the most useful additional information. Monte Carlo simulation studies on some typical scenarios were performed, and the results indicate that the estimation errors are commensurate with the theoretical lower bounds, thus illustrating that the proposed estimators are efficient     

GPS和GLONASS广播星历参数分析及算法

GPS和GLONASS作为当今世界上在轨运行的两大卫星导航系统,其广播星历参数的设计和算法各具特点。本文探讨了GPS和GLONASS广播星历参数设计的物理背景,对它们各自的特征进行了分析比较,最后文章给出了GPS广播星历参数的一种拟合算法。     

An LS-TLS-based sequential identification algorithm: Application toan accelerometer

Total least squares (TLS) parameter estimation is an alternative to least squares (LS) estimation when there are errors in both data matrix and observation vector. Especially, when some of the columns, not all, of the data matrix A are free of error, we call it a mixed LS-TLS problem. Accordingly, a sequential algorithm for solving a mixed LS-TLS problem is proposed here. The proposed algorithm employs an efficient algorithm to locate the minimum eigenpair, instead of singular value decomposition (SVD) which is computationally exacting. The proposed algorithm is applied to an accelerometer model to identify error parameters which are very important in inertial navigation systems (INS)