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.     

分布式航空电子系统信息传输机构设计研究

 航空电子系统日益增长的复杂性使其必须走向分布式处理的道路。本文介绍一个基于1553B总线的分布式航空电子系统的实验模型——EPDAS系统,讨论了EPDAS系统信息传输机构的有关组成部分:总线通信协议、通信管理软件和总线接口,本文在分析传统的同步总线控制方式的缺点之后,提出了询问和命令/响应相结合的总线控制方式,该方式能提高总线传输的效率和实时性。在EPDAS系统的总线接口设计中,引入了流水线并行处理技术,解决了总线接口的瓶颈问题,并使之易于VLSI化;伪DMA控制的概念,使总线接口电路更加简化;共享存贮器的互连技术,具有效率高、控制简单、容易实现等优点。EPDAS系统结构合理、效率高,符合国情、适合于新一代的飞机。     

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     

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.     

An Upper Bound on Detection Probability for Fluctuating Signals

In the theory of signal detectability, the signal-to-noise ratio (SNR), defined as the quotient of the average received signal energy and the spectral density of the white Gaussian noise, is a fundamental parameter. For a signal which is exactly known, or known except for a random phase, this ratio uniquely defines the detection performance which can be achieved with a matched filter receiver. However, when the signal amplitude is a random parameter, the detection performance is changed and must be determined from the probability density function (pdf) of the amplitude. Relative to the case of a constant signal amplitude, such signal amplitude fluctuation usually degrades performance when a high probability of detection (Pd) is required, but improves performance at low values of Pd; the corresponding change in the required SNR is the so-called signal fluctuation loss Lf. Thus, since Lf in some cases represents an improvement in performance for low values of Pd, a question of at least theoretical interest is: how large might this improvement be, when the class of all signal amplitude pdf's is considered. The solution, presented here, results in a lower bound on the signal fluctuation loss Lf as a function of Pd, or equivalently an upper bound on Pd as a function of SNR. The corresponding most favorable pdf was determined using the Lagrange multiplier technique and results of a numerical maximization are included to provide insight into the general properties of the solution.