Accuracy and Error Sens-itivities for Circular Scan Correlator Systems

Correlation guidance systems are being developed and implemented as a means of improving the performance of tactical and strategic missiles. Performance predictions for these systems often neglect the actual correlator structure due to the mathematical difficulties associated with analyzing practical operating correlation systems. In this paper accuracy predictions and error sensitivities to systematic error sources are presented for a circular scan correlation system using the tracking form of the modified difference squared correlation algorithm. In addition, the sine/cosine modulation required to generate the X and Y tracking commands is considered, as well as unequal range and azimuth resolution. The techniques developed to perform this analysis can be easily applied in a simplified fashion to noncircular scan systems and to correlators using a product correlation algorithm.     

The Performance of Analog Correlators for Several Integrator Functions

A measure of analog correlator performance is considered and interpreted reted as an output signl-to-noise ratio. This quantity is shown to depend on the fourth-order expectation of the input signals and the characteristics of the integrating system. Based on the output signal-to-noise ratio, figures of merit are established for correlators utilizing an ideal low-pass filter, an RC filter, and a finite time integrator. These figures of merit indicate to what degree the correlators reject noise components. For jointly Gaussian inputs, the variation of the output signal-to-noise ratio with the input signal-to-noise ratio is shown to be independent of the integrating system. Finally, a graphical comparison indicates the characteristics of the three systems for several different parameters. This comparison shows that the finite time integrator is superior to the other two systems considered.     

Gating Functions for Multipath Mitigation in GNSS BOC Signals

A new multipath mitigation technique is proposed for binary offset carrier (BOC) signals in global navigation satellite systems (GNSS) using the concept of gating function originally conceived for the GPS coarse-acquisition (C/A) code. Specially-tailored pulses are utilized to diminish the number of false-lock points of the code discriminator response and to improve the multipath mitigation capability. The code loop includes only four real correlators (two extra correlators are required for the simplified bump-jumping algorithm with BOC(n,n) signals). Results obtained with BOC(n,n) and BOC(2n,n) signals show that this technique eliminates the multipath ranging errors for reflected rays with relative delays typically above twenty percent of the spreading code chip duration, thus comparing favorably with the conventional receiver correlation techniques.     

A noise insensitive solution to an ambiguity problem in spectralestimation

The instantaneous frequency measurement (IFM) receiver is capable of measuring the center frequency of single frequency pulses over a wide range (bandwidth) of center frequencies. Because of various constraints, the frequency resolution requirement results in long correlator delay times that reduce the single correlator bandwidth. A large bandwidth can be achieved only if two or more correlators are used. The problem of estimating frequency is then reduced to the simultaneous congruence problem of number theory. A design procedure is presented for solving the congruence problem for a given amount of noise protection, a stated frequency resolution, a minimum bandwidth, and a fixed level of precision (bits) in the IFM receiver     

CFAR detection in clutter with unknown correlation properties

We develop a constant false-alarm rate (CFAR) approach for detecting a random N-dimensional complex vector in the presence of clutter or interference modeled as a zero mean complex Gaussian vector whose correlation properties are not known to the receiver. It is assumed that estimates of the correlation properties of the clutter/interference may be obtained independently by processing the received vectors from a set of reference cells. We characterize the detection performance of this algorithm when the signal to be detected is modeled as a zero-mean complex Gaussian random vector with unknown correlation matrix. Results show that for a prescribed false alarm probability and a given signal-to-clutter ratio (to be defined in the text), the detectability of Gaussian random signals depends on the eigenvalues of the matrix R_c^-1R_s. The nonsingular matrix R_c and the matrix R_s are the correlation matrices of clutter-plus-noise and signal vectors respectively. It is shown that the “effective” fluctuation statistics of the signal to be detected is determined completely by the eigenvalues of the matrix R_c^-1R_s. For example the signal to be detected has an effective Swerling II fluctuation statistics when all eigenvalues of the above matrix are equal. Swerling I fluctuation statistics results effectively when all eigenvalues except one are equal to zero. Eigenvalue distributions between these two limiting cases correspond to fluctuation statistics that lie between Swerling I and II models     

Image Correlation with Geometric Distortion Part 1: Acquisition Performance

The degradation in acquisition probability that occurs when cross correlation is used to determine the offset of two images of the same scene that differ by a relative geometric distortion is presented. The geometric distortions considered can be represented by a general affine transformation of image coordinates. The analysis shows that for a given geometric distortion there is an image size and shape that minimizes the probability of false acquisition. The results are derived for images modeled as random patterns with arbitrary auto-correlation functions. The results are illustrated for images with Gaussian autocorrelation functions.     

太阳能火箭发动机聚光器设计方法

对工程上常用聚光器进行了性能比较,得出了适合于太阳能火箭发动机(STP)的聚光器及其具有的性能优点,研究了此种聚光器的的设计方法,并推出了相关公式和其中的关键技术,这对STP聚光器的工程设计具有重要的指导价值。      

On the Mean Frequency Measurement System Using Correlation Detection

This paper is concerned with the problem of measuring the mean frequency of the power spectrum of a zero-mean, stationary, narrowband Gaussian random signal in the presence of additive Gaussian noise. Signal-to-noise ratios at the output of the mean frequency measurement system using correlation detection are analyzed in terms of input signal-to-noise ratio, input signal and noise bandwidths, and integration time. The results obtained are verified experimentally, and a comparison with a conventional zero-crossing detector is also made.     

Multipath Effects on an Azimuthal Monopulse System

The first topic considered is an analysis of the conditions under which the conventional definition of length of the glistening surface, as given by Beckmann and Spizzichino, is not valid. For some conditions, significant amounts of incoherent scattered power can be received from areas beyond the conventional length. A second topic is the investigation of the effect on azimuthal angular tracking accuracy due to such scattering factors as shadowing, surface height distribution, standard deviation in surface height ?, surface correlation length T, unevenness and inhomogeneity of the terrain, antenna heights, and signal polarization. A number of interesting results have been observed. The amount of additional incoherent power not included under the conventional definition depends on the ratio ?/T, except for the case where both transmitter and receiver are very close to the surface. The trends in the behavior of the glistening surface are similar for vertical or horizontal polarization, for Gaussian or exponential surface height distributions, and for different signal frequencies in the S-band to L-band range.     

用卡尔曼滤波器估计目标机动加速度

为了使基于线性二次型高斯理论的LQG最优制导规律得到工程应用，设计了一种寻的回路中的卡尔曼滤波器，利用仿真技术，用这种滤波器对目标机动加速度进行了估计，仿真结果表明，这种滤波器可以准确估计目标机动加速度。     

Correlated K-distributed clutter generation for radar detection andtrack

The generation of correlated vectors for non-Gaussian clutter is considered for log normal, Weibull, and K-probability distributions. Previous results for log normal and Weibull distributions are summarized. Expressions for the probability distributions and moments of K-distributed clutter of any correlation are derived. Procedures for forming samples of each type of clutter are shown to be equivalent to passing white Gaussian noise through a linear filter followed by a nonlinear operation. Curves of correlation coefficients necessary for the simulation of these vectors are presented for each distribution     

现代战机最佳导引算法研究

针对现代战机向目标空域的导引过程,建立了载机与目标相对运动的数学模型。基于最优控制的相关理论,以导引的准确性和控制的经济性为性能指标,建立了飞机导引控制算法。该导引算法既考虑了导引的角度误差又考虑了目标线角速度误差,通过对所得到的导引算法进行仿真验证,表明所得到的导引算法具有较强的适应性,能够满足飞机的导引要求。     

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.     

Performance complexity study of several approaches to automatictarget recognition from SAR images

A framework which allows for the direct comparison of alternate approaches to automatic target recognition (ATR) from synthetic aperture radar (SAR) images is described and applied to variants of several ATR algorithms. This framework allows comparisons to be made on an even footing while minimizing the impact of implementation details and accounts for variation in image sizes, in angular resolution, and in the sizes of orientation windows used for training. Alternate approaches to ATR are characterized in terms of the best achievable performance as a function of the complexity of the model parameter database. Several approaches to ATR from SAR images are described and the performance achievable by each for a range of database complexities is studied and compared. These approaches are based on a likelihood test under a conditionally Gaussian model, log-magnitude least squared error, and quarter power least squared error. All approaches are evaluated for a wide range of parameterizations and the dependence on these parameters of both the resulting performance and the resulting database complexity is explored. Databases for all of the approaches are trained using identical sets of images and their performance is assessed under identical testing scenarios in terms of probability of correct classification, confusion matrices, and orientation estimation error. The results indicate that the conditionally Gaussian approach outperforms the other two approaches on average for both target recognition and orientation estimation, that accounting for radar power fluctuation improves performance for all three methods, and that the conditionally Gaussian approach normalized for power delivers average performance that is equal or superior to all other considered approaches     

基于纹理合成优化算法的多相非均质材料二维微观结构表征与重建

材料微观结构表征与重建(Microstructure characterization and reconstruction,MCR)可用于建立加工-结构-属性(Processing-Structure-Property,PSP)关系,已成为计算材料学与材料设计的研究重点.通过阈值分割将多相非均质材料的金相照片识别为由...     

多个空间高斯源信号情况下成组三维图像特征提取方法

针对功能磁共振成像数据中含有多个高斯信号源的盲源分离问题,介绍了一种成组典型相关分析方法(Group BSS-CCA)。这个方法的组分析框架参照了GIFT工具箱中的Group ICA算法,具体的典型相关分析方法应用的是Friman等人提出的BSS-CCA算法。以验证该方法的有效性为目的,设计了仿真实验;结果表明,该方法能较好识别出混合在人脑功能磁共振成像数据的2个空间高斯信号。Group BSS-CCA算法对研究人脑的功能磁共振成像数据具有较高的实用价值。     

Performance of a Mean Level Detector Processing M-Correlated Sweeps

The performance of a mean level detector processing M-correlated consecutive sweeps is derived. Performance when sweeps are independent can be obtained simply as a special case. The background noise is assumed stationary Gaussian and pulses are fluctuating according to the Swerling I model. Results are obtained for both finite and infinite reference noise samples. It is shown that for fixed M the relative improvement over the single hit case increases when the correlation between sweeps decreases and as the probability of false alarm is kept at lower rates.     

SAR ATR performance using a conditionally Gaussian model

A family of conditionally Gaussian signal models for synthetic aperture radar (SAR) imagery is presented, extending a related class of models developed for high resolution radar range profiles. This signal model is robust with respect to the variations of the complex-valued radar signals due to the coherent combination of returns from scatterers as those scatterers move through relative distances on the order of a wavelength of the transmitted signal (target speckle). The target type and the relative orientations of the sensor, target, and ground plane parameterize the conditionally Gaussian model. Based upon this model, algorithms to jointly estimate both the target type and pose are developed. Performance results for both target pose estimation and target recognition are presented for publicly released data from the MSTAR program     

Detection probabilities for correlated Rayleigh fading signals

Both the method of saddlepoint integration and its associated saddlepoint approximation are applied to calculating the probability of detecting correlated Rayleigh-fading signals in Gaussian noise by means of a detector that integrates M samples of the output of a quadratic rectifier. The quadrature components of the signal samples are modeled as an autoregressive moving-average process, and specific results are exhibited for a first-order Markov process. By these methods the fluctuation loss can be computed for much larger values of M and for larger values of the detection probability than previously. Values calculated by the saddlepoint approximation prove to be close enough to the exact values to be useful over a broad range of signal parameters     

LQG Guidance Law with Bounded Acceleration Command

A novel missile guidance law that is dependent on the conditional probability density function of the estimated states is presented. The guidance law is derived by analyzing an interception scenario in the framework of an linear quadratic Gaussian (LQG) terminal control problem with bounded acceleration command. The nonlinear saturation function is represented by the equivalent random input describing function. Since for the investigated problem the certainty equivalence property is not valid, the resulting controller depends on the measurement noise level and on the saturation limit. In comparison to the classical optimal guidance law (OGL), the maximal value of the effective navigation gain is achieved during the engagement instead of near the terminal time. Thus, the saturation limit is reached earlier so as to have enough time to reduce the guidance errors. Using Monte-Carlo simulations, the superiority of the new guidance law over the classical OGL is shown. This validates the new approach of designing an estimation statistics dependent guidance law by using a random input describing function to approximate the missile's acceleration saturation.