Track-While-Scan Algorithm in a Clutter Environment

A track-while scan (TWS) algorithm is developed for targets in a clutter environment. The problem has been studied using only the position measurements [1, 5-8], but the simulation results have not been satisfactory. Modern processing techniques (FFT processor) ) in air traffic control and surveillance radar receivers provide both position and radial velocity. The radial velocity measurement may be conveniently used in the target-track correlation process, which will reduce the association ambiguity in the clutter environment. t. In the clear environment the algorithm using the position and radial velocity measurements has been treated in [3, 4]. A TWS algorithm, using both position and radial velocity measurements for targets in a clutter environment, is presented here. The algorithm obtained is nonlinear and adaptive. In order to evaluate the improvement due to radial velocity measurement a simulation has been performed on a digital computer. The algorithm was run with and without radial velocity measurements to compare its performances. An improvement was noted especially when the target path included an accelerated portion.     

A Detection Algorithm for Optical Targets in Clutter

There is active interest in the development of algorithms for detecting weak stationary optical and IR targets in a heavy opticalclutter background. Often only poor detectability of low signal-to-noise ratio (SNR) targets is achieved when the direct correlation method is used. In many cases, this is partly obviated by using detection with correlated reference scenes [1, 2].This paper uses the experimentally justified assumption that most optical clutter can be modeled as a whitened Gaussian randomprocess with a rapidly space-varying mean and a more slowlyvarying covariance [2]. With this assumption, a new constant falsealarm rate (CFAR) detector is developed as an application of the classical generalized maximum likelihood ratio test of Neyman and Pearson. The final CFAR test is a dimensionless ratio. This test exhibits the desirable property that its probability of a false alarm(PFA) is independent of the covariance matrix of the actual noiseencountered. When the underlying noise processes are complex intime, similar considerations can yield a sidelobe canceler CFARdetection criterion for radar and communications. Performance analyses based on the probability of detection (PD)versus signal-to-noise ratio for several given fixed false alarm probabilities are presented. Finally these performance curves are validated by computer simulations of the detection process which use real image data with artificially implanted signals.     

DO 28飞行试验数据一致性检验

 本文研究DO28试验机飞行试验数据一致性检验及其误差校正。建立了由非线性运动学方程及内容广泛的校正环节构成的一致性检验模型,解决了大地风场重构、测量信号时间延迟估计、ψ转换及测量控制信号的校正。为DO28参数估计提供了可靠、准确的飞行试验数据。     

Single-phase power distribution system power flow and faultanalysis

Alternative methods for power flow and fault analysis of single-phase distribution systems are presented. The algorithms for both power flow and fault analysis utilize a generalized approach to network modeling. The generalized admittance matrix, formed using elements of linear graph theory, is an accurate network model for all possible single-phase network configurations. Unlike the standard nodal admittance matrix formulation algorithms, the generalized approach uses generalized component models for the transmission line and transformer. The standard assumption of a common node voltage reference point is not required to construct the generalized admittance matrix. Therefore, truly accurate simulation results can be obtained for networks that cannot be modeled using traditional techniques     

环向圈连带冠叶片的动态分析

 本文将动态子结构方法中链式加载技术与群论算法相结合,提出环向固连带冠叶片动力特性分析的一种新方法。文中列出了分析步骤与具体公式,并有实例的计算结果。该方方法适用于研究具有带冠叶片的单级转子中,“冠”的整体效应。     

An Adaptive Array Signal Processing Algorithm for Communications

An algorithm is described for initial synchronization in a communication system with a digital adaptive array. This algorithm can also be used for message extraction. A set of consecutive complex video samples of the array output is processed to obtain optimum adaptive array weights, based on a least mean square (LMS) error criterion. This computation is performed for each of the possible alternative signals which may be present during an observation interval. The correct synchronization time or message symbol is selected as the one which yields the minimum LMS error. Assuming orthogonality of the alternative codes, a probability distribution for the output of this processor has been derived.     

Optical identification of X-ray sources in the Einstein observatory medium and deep surveys

Methods are discussed for establishing the optical identification of X ray sources in the medium and deep X-ray surveys of the Einstein Observatory. Of the 63 X-ray sources with a statistical significance of 5 in the medium survey (Maccacaro et al. 1981), optical identification work is summarized for 51, of which identifications have been made with 30 active galactic nuclei. The optical properties of some of these X-ray selected objects are briefly discussed.The Einstein deep survey of Pavo (Griffiths et al. 1981) is used to illustrate the problems and methods used for securing optical identifications for X-ray sources in the deep survey fields. Identifications have been made with 4 QSOs at the bright end of the optical candidate distribution (together with 3 G stars) and it is shown that a further 7 fainter objects are also likely to be QSOs.     

Some crucial X-ray observations — One or two SNR(s) in Crux?

A new EXOSAT (LE/CMA) observation of the region in Crux (R.A. 11h 45m, Dec. -62°) where Markert et al. (1981) reported the existence of two x-ray SNR's is presented. After cleaning the CMA field from the point source component, due to the UV emission of the numerous stars in the field, the smoothed x-ray contours are compared to the 408 MHz radio map of Caswell et al. (1983). The existence of two, well-separate x-ray emission regions is confirmed by EXOSAT, and the current x-ray/radio picture is not sufficent to distinguish clearly between the assumption of one or two (possibly interacting) SNR's in the region.