基于Laguerre函数的高压力非线性传感器补偿研究

针对高压力传感器线性化输出的结果不准确的现象,研究了具有针对性的Duffing非线性系统。用传感器的输出数据作为补偿器的输入,传感器的输入数据作为补偿器的输出,进行基于Laguerre函数的非线性动态补偿器的设计研究。该方法无需知道传感器的非线性阶数,对于外界干扰有较强的抑制作用,对于时延对象也具有一定的优势。利用该补偿器对传感器进行动态补偿,将补偿结果与阶跃响应输出进行对比,结果表明该非线性模型补偿的有效性。     

结构动力学与颤振约束下无人机机翼优化设计

提出了同时考虑结构动力学约束和颤振约束的优化设计方法，建立了利用规划优化算法求解问题的流程，并将其融入大型CAE软件系统HAJIF2013中，研究了优化问题中目标函数和约束条件的选取方式。以某型无人机机翼颤振模型为算例，利用拉盖尔迭代方法自动计算颤振速度，并对优化算法的有效性进行了验证。研究表明，所提出的优化设计方法有效，实现了整个优化求解流程的自动化，对工程设计具有指导意义。     

Distribution of the envelope of a sum of random sine waves andGaussian noise

The cumulative distribution of the envelope of the sum of a sinusoidal signal, a number M of randomly phased interfering sine waves, and, possibly, Gaussian noise is expressed as the sum of Marcum's Q-function and an asymptotic series of Laguerre polynomials, much like the ordinary Edgeworth series for the distribution of the sum of a number of independent random variables. A test of the method with M=20 showed that its computation requires about 2% of the time needed for numerical inversion of the characteristic function of the distribution     

Estimating Target Lengths Shorter Than the Radar Pulse Width

This paper discusses the performance and sensitivity of a maximum-likelihood length estimation algorithm which was originally developed to estimate the separation between unresolved point scatterers. It shows that when the two-scatterer target model is valid, the algorithm reliably estimates lengths shorter than the Rayleigh limit provided that the strength of no third interior scatterer (or its equivalent created by a few very closely spaced scatterers) is greater than the geometric mean of the strengths of the fore and aft scatterers.     

An algorithm for detection of moving optical targets

An algorithm is described for detecting moving optical targets against spatially nonstationary Poisson background and noise. The algorithm has applications in optical detection of objects such as meteors, asteroids, and satellites against a stellar background. A maximum-likelihood approach is used which results in reducing interference from stars. It is shown that by choosing a detection threshold to provide a constant false alarm rate, the resulting algorithm is independent of the signal strength of the target. An analysis of this algorithm is presented, showing the probability of detection for several false-alarm rates     

False alarm control using Doppler estimation

A technique which uses maximum-likelihood estimates (MLEs) of target Doppler and target amplitude is developed for rejecting clutter residues. Multiple estimates are made and consistency checks are applied to the estimates. Simulation results indicate that for large clutter-to-noise ratios (C/N⩾55 dB) the probability of false alarm from clutter residues is reduced from 1.0 to below 0.01     

Approximate Evaluation of Detection Probabilities in Radar and Optical Communications

Cumulative probability distributions such as occur in radar detection problems are approximated by a new version of the saddlepoint method of evaluating the inverse Laplace transform of the moment-generating function. When the number of radar pulses integrated is large, the approximation of lowest order yields good accuracy in the tails of the distributions, yet requires much less computation than standard recursive methods. Greater accuracy can be achieved upon summing the residual series by converting it to a continued fraction. The method is applied to evaluating the error-function integral and the Mth-order Q function, and to approximating the inverse of the chi-squared distribution. Cumulative distributions of discrete random variables, needed for determining error probabilities in optical communication receivers that involve counting photoelectrons, can be approximated by a simple modification of the method, which is here applied to the Laguerre distribution.     

The Detection Performance of the Siebert and Dicke-Fix CFAR Radar Detectors

The Siebert and the Dicke-fix CFAR radar detectors, used to maintain a constant false alarm rate (CFAR) in radar receivers under very similar circumstances, are considered. The Siebert detector represents the maximum-likelihood detection procedure for a signal in Gaussian noise of unknown power level, whereas the Dicke-fix makes use of a bandpass limiter to normalize the input and thus ensure a constant false alarm rate. The detection performance of the two detectors is determined and a comparison shows that over a wide range of parameters, the Dicke-fix introduces a loss which is approximately 1 B larger than for the Siebert detector.     

Localization performance of arrays subject to phase errors

The passive localisation of radiating sources using an array subject to random perturbations in sensor phases is presented. All source signals as well as additive noises observed at the sensors are assumed to be independent identically distributed zero-mean Gaussian random processes. Cramer-Rao bounds are derived for source bearings and ranges for the phase errors at each sensor. It is shown that accurate phase calibration can be achieved when the number of sources exceeds a certain minimum. The locations of the calibrating sources need not be known a priori and need only satisfy mild regularity conditions. A calibration procedure is proposed which uses maximum-likelihood techniques     

Low-Angle Radar Tracking in the Presence of Multipath

This paper is concerned with the problem of tracking radar targets in the low-angle regime where conventional tracking radars encounter difficulty due to the presence of a surface-reflected ray. Starting with a classical maximum-likelihood analysis of the problem of two closely spaced targets, two different techniques are evolved which are theoretically capable of dealing with the multipath problem. The expected accuracy has been studied both analytically and by means of computer simulations. Experimental programs have demonstrated the feasibility of both techniques. The paper also includes a discussion of certain alternative solutions to the problem.     

Extended solution to multiple maneuvering target tracking

An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the one-step conditional maximum-likelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. With this approach, data-association and target maneuvering problems can be solved simultaneously. Detailed Monte Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions     

Time delay estimation at high signal-to-noise ratio

The estimation of the delay between two signals is examined in the limit of high signal-to-noise ratio (SNR). It is shown that for the case of white noise, cross correlation with no prefiltering approaches the optimal maximum-likelihood (ML) estimator as the SNR grows to infinity. In simulation experiments with SNRs greater than 1, it outperforms the approximate ML estimator, which is based on estimated spectra. Other algorithms, such as generalized cross correlation or parameter estimation algorithms, are shown to be suboptimal at high SNRs     

Maximum likelihood azimuth estimation applied to SSR/IFF systems

A conventional (nonmonopulse) secondary surveillance radar (SSR) is significantly cheaper than a monopulse SSR but exhibits much greater azimuthal error, especially when some of the replies are missing. Estimation techniques and their performance are discussed with special reference to SSR applications, and a novel estimator for conventional SSR is described. The proposed technique is a close approximation of the maximum-likelihood estimator (MLE), taking into account the receiver characteristics as well as the missed replies. Estimator performance obtained by analysis and computer simulation is compared with that of conventional estimators that are based on the leading and trailing edges of binary sequences and shows significantly improved accuracy     

Nonuniform array processing via the polynomial approach

A polynomial approach for maximum-likelihood (ML) estimation of superimposed signals in time-series problems and array processing was recently proposed. This technique was applied successfully to linear uniform arrays and to uniformly sampled complex exponential signals. However, uniformly spaced arrays are not optimal for minimum variance estimation of bearing, range or position, and uniform sampling of signals is not always possible in practice. The authors make use of the expectation-maximization algorithm to apply the polynomial approach to sublattice arrays and to missing samples in time-series problems     

Self-calibrating SSR monopulse receiver

An extension of the monopulse technique for estimating the target azimuth in a secondary surveillance radar (SSR) is considered. The idea is to associate in pairs monopulse measurements coming from the amplitude processor (AP) at the dwell time processing level. This allows the automatic compensation of the bias errors due to the misalignments in the receiver channels, thus eliminating the necessity for periodic system calibration. This dual-pulse technique also allows for the practical use of the dot product receiver as a modification of the AP receiver. This, in turn, implies that the variance of each dual-pulse estimate is uniformly maintained at the monopulse maximum-likelihood level over the whole off-boresight angle (OBA) range     

A method for estimating parameters of K-distributed clutter

A method for estimating the parameters of K-distributed clutter when the available sample size of the data is limited is proposed. In this method, the arithmetic mean and geometric mean of the given data are used to estimate the model parameters. Expressions characterizing the performance of the proposed estimator are presented, along with some simulation results. For spiky clutter, simulations show that parameter estimates obtained from the arithmetic and geometric mean are approximately equal to the numerically evaluated maximum-likelihood (ML) estimates. The method is also used to estimate the parameter of the Weibull density     

国产材料疲劳寿命分布参数α的初步估计

 <正> The fatigue-tested data of home-made materials and simple structure data are collected, which consist of 488 groups of 2705 specimens for aluminum alloys ; 313 groups of 1798 specimens for alloy steels) 79 groups of 389 specimens for titanium alloys. The shape parameter a of two-parameter Weibull distribution is estimated with maximum-likelihood estimation method and the preliminary estimation of a is given. In this study, the estimated parameters of home-made materials coincide with the parameters of overseas materials and the parameters a suggested by the literature can be applied to home-made material, too. This work also studies the effects of stress concentration factor ranges of fatigue life and tensile strength of materials on the values of a.     

Constant-False-Alarm-Rate Signal Processors for Several Types of Interference

Distribution-free methods and maximum-likelihood estimation technique have been previously suggested for constant-false-alarm-rate (CFAR) processors. The first technique assumes no a priori environmental knowledge and the second assumes almost complete environmental knowledge. Several intermediate environmental assumptions are considered. The performance of single-pulse transmission signal processors that produce CFAR for the different environments is analyzed. Probability of target detection is evaluated for Rayleigh interference and Swerling I target. It is shown that adaptive threshold techniques implemented by logarithmic amplifiers, instead of linear amplifiers, can attain better false-alarm-rate control with only small loss in target detectability.     

Efficient dynamic programming in presence of nuisance parameters

The dynamic programming approach for maximum a posteriori (MAP) estimation of Markov sequences is frequently proposed for problems in control theory, communications, and signal processing. It is usually assumed that the observation sequence is a perfectly known function of the Markov sequence of interest, except for some additive noise with known statistics. However, often the observation is not only a function of the Markov sequence but also of a vector of unknown nuisance parameters. It is shown how the dynamic programming methodology can be extended to estimate both the nuisance parameters and the Markov sequence, using a combined maximum-likelihood and MAP framework. The technique is efficient relative to other possible solutions. The problem of detecting and tracking moving targets observed by imaging sensors is used to demonstrate the efficiency of the procedure     

Optimum Position Estimation Using Multiple-Frequency Omega

The maximum-likelihood estimator of the line of position (LOP) resulting from K frequencies received from each of two Omega stations for high SNR is derived. The estimator takes advantage of interfrequency correlation of phase uncertainties by modeling them as resulting from phase velocity uncertainties which are jointly Gaussian with known covariance. The utilization of Omega for search and rescue systems is examined. For this application, the result of increasing the size of the unambiguous lanes of Omega by addition of a fourth frequency to the present three-frequency format is examined. The results of Monte Carlo simulation, performed for several easily implemented fourth frequencies, are presented. The simulation results illustrate the extent to which lane errors can be expected as a function of various fourth frequencies, phase velocity uncertainties, and SNR.