一种基于空间到达角的卫星电子侦察信号分选方法

在建立简化的卫星电子侦察空间模型的基础上，提出了一种利用空间到达角分选卫星电子侦察信号的新方法。通过仿真实验验证了这种方法的可行性。该方法可用于密集信号的预处理。     

Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

基于WVD的防空雷达直升机信号特征分析

基于直升机目标旋转部件的调制模型，本文针对防空雷达提出了分析直升机信号特征的一种新方法——WVD法，并对直升机目标旋转部件调制回波信号在不同噪声情况下加以仿真分析，结果表明：用WVD分析雷达回波中直升机信号特征是一种非常有效的方法。     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

无线电引信多普勒信号增速器的研究

论述了无线电引信多普勒信号增速器的实现原理及意义，介绍了采用ＴＭＳ３２０Ｃ３０作为ＣＰＵ、多片大容量静态ＲＡＭ芯片构成海量存储体的信号增速器硬件结构和软件设计，并提出了今后的研究方向。     

窄带中频数字接收机高速信号处理技术

窄带中频数字接收机在雷达对抗侦察中得到了广泛应用，其高速信号处理技术是目前研究的重点。本文详细介绍了数字雷达告警接收机高速信号处理技术的发展现状和关键技术，最后通过对该技术的全面分析指出了值得深入研究的领域。     

二次型时频分析技术的开发与应用

基于二次型的时频分析是高分辨率时频分析技术的有效方法之一，该项技术能够有效反映时变信号的频谱特性，具有分辨率高、能量集中和跟踪瞬时频率的特点。从时变信号的特点出发，阐述了二次型时频分析技术的基本方法原理，采用正演模型分析验证了该方法的有效性，并在实际地震资料中应用于识别物源方向、划分沉积相带、预测储层结构以及相对厚度等诸多方面，均取得了较好的效果。     

CLP(ℜ) and some electrical engineering problems

The Constraint Logic Programming Scheme defines a class of languages designed for programming with constraints using a logic programming approach. These languages are soundly based on a unified framework of formal semantics. In particular, as an instance of this scheme with real arithmetic constraints, the CLP() language facilitates and encourages a concise and declarative style of programming for problems involving a mix of numeric and non-numeric computation.In this paper we illustrate the practical applicability of CLP() with examples of programs to solve electrical engineering problems. This field is particularly rich in problems that are complex and largely numeric, enabling us to demonstrate a number of the unique features of CLP(). A detailed look at some of the more important programming techniques highlights the ability of CLP() to support well-known, powerful techniques from constraint programming. Our thesis is that CLP() is an embodiment of these techniques in a language that is more general, elegant and versatile than the earlier languages, and yet is practical.An earlier version of this paper appeared in the proceedings of the 4th International Conference on Logic Programming, Melbourne, May 1987. Much of this work was carried out while the authors were at Monash University, Melbourne, Australia.     

A METHOD FOR GENERATING INDEPENDENT REALIZATIONS OF A MULTIVARIATE NORMAL STATIONARY AND INVERTIBLE ARMA(p, q) PROCESS

Abstract. A method for generating finite independent realizations of a normal multivariate stationary ARMA( p, q ) process is proposed. It is based on an AR (1) representation of an ARMA( p, q ) process allowing for an exact generation of the initial values of the simulation algorithm. Input facilities are supplied in order to assure stationarity and invertibility of the considered process.     

TESTS FOR FRACTIONAL INTEGRATION:A MONTE CARLO INVESTIGATION

Abstract. The performance of the Geweke-Porter-Hudak (GPH) test, the modified rescaled range (MRR) test and two Lagrange multiplier (LM) type tests for fractional integration in small samples is examined using Monte Carlo methods. Both the GPH and MRR tests are found to be robust to moderate autoregressive moving-average components, autoregressive conditional heteroskedasticity effects and shifts in the variance. However, these two tests are sensitive to large autoregressive moving-average components and shifts in the mean. It is also found that the LM tests are sensitive to deviations from the null hypothesis. As an illustration, the GPH test is applied to two economic data series.