短序列条件下基于分段多项式建模方法的相位估计性能分析

该文主要对短序列非多项式相位条件下基于高阶模糊函数(HAF)的多项式相位系数估计算法性能进行了较详细的讨论。进一步研究了基于这种算法思想的分段多项式相位建模的瞬时相位估计方法。该方法的思想主要体现为将需估计数据序列进行分段,每个短数据段的瞬时相位采用一个低阶的多项式来逼近,而这些逼近多项式的各阶系数利用HAF或乘积高阶模糊函数(PHAF)的方法进行估计,最终整个数据序列的相位由各段估计出的瞬时相位合并而成。该方法的估计性能很大程度上取决于各分段数据序列的估计精度。文中分析了短序列非多项式相位对HAF及PHAF的影响,并通过仿真实验给出了具有一般性的结论。     

基于HAF估计的超宽带LFM信号距离像频域校正

为更准确且简洁地表达超宽带的线性调频(LFM)信号的非线性相位,文中采用一种高阶模糊函数,而不是经典的泰勒展开来表达非线性相位多项式,并用高阶模糊函数(HAF)法估计非线性相位多项式系数。针对因目标延时不同导致的非线性程度不同的问题,采用了一种频域校正法补偿回波的非线性相位,一次性完成不同距离目标的一维距离像聚焦,无需对不同距离目标分别进行校正处理,算法效率大大提高。     

基于多尺度线调频基信号稀疏分解的 信号分离和瞬时频率估计

提出了一种基于多尺度线调频基信号稀疏分解的多分量多项式相位信号分离和瞬时频率估计方法.该方法采用多尺度的线调频基函数对多分量多项式相位信号进行投影分解,通过从不同的时间支撑区内投影系数最大的基函数中寻找出使分解信号能量最大的基元函数组合,逐次获得信号包含的能量最大的多项式相位信号分量,从而实现多分量多项式相位信号的分离,而从基元函数连接形成的频率曲线则可获得多项式相位信号分量瞬时频率的估计.仿真信号分析表明,本文方法能在信噪比较低情况下有效分离多分量多项式相位信号中包含的多项式相位信号分量,准确地估计其瞬时频率.     

多分量多项式相位信号的参量估计

本文首先分析了现有的基于PHAF估计mc-PPS相位参量方法的局限性.提出了先由对应于不同时间延迟参数的高阶模糊度函数估计出一组相位系数估值,然后采取表决方法从该组估值中提取出最终相位系数估值的参量估计方法.该方法既回避了信号检测中的阈值选取问题,又提高了检测可靠性及参量估计精度.仿真实验验证了本文方法的有效性.     

分数阶傅里叶变换的多项式相位信号DOA估计

针对多项式相位信号波达方向(DOA)估计研究较少的问题,提出了一种基于分数阶傅里 叶变换(FRFT)的多项式相位信号(PPS)的DOA估计算法。该算法首先通过多项式相位变换,估 计出PPS的最高阶相位系数,从而可以消除最高阶项。运用这一降阶思想,依次消除高阶项 ,这样PPS可降为线性调频(LFM)信号,然后将宽带的LFM信号转化为分数阶Fourier域窄带的 平稳信号。在相应的分数阶Fourier域,运用求根MUSIC算法对信号进行DOA估计,从而把LFM 信号的DOA估计推广到了PPS的DOA估计。理论分析和仿真实验表明,该方法能很好地估计出P PS的DOA,并且简洁。     

多项式建模解电离层相位污染阶数选择新方法

电离层相位污染使天波超视距雷达杂波频谱展宽,影响舰船等低速目标检测.针对这一问题,近年来发展了基于分段多项式相位建模和高阶模糊函数的(HAF)解电离层污染算法,如何合理地选取模型阶数是该算法的核心.给出了两种改进的自适应多项式建模阶数选择方法.并利用仿真方法进行了验证,结果表明:基于高阶模糊函数变换性质的频域和时域阶数选择方法的计算量较现有算法有较大提高,且频域法可在较低信噪比下准确判断多项式阶数.     

L波段雷达电离层高速运动目标ISAR成像补偿方法

目标高速运动和电离层效应都会对低频段宽带线性调频雷达信号的相位产生调制现象,进而降低逆合成孔径雷达(ISAR)成像分辨率。为得到清晰的目标ISAR图像,需有效消除这两者对目标回波的影响。该文首先建立电离层高速运动目标回波的信号模型,再根据目标回波为高阶多项式相位信号的特点,提出基于离散多项式变换的高阶相位估计算法,利用高阶相位估计值进行回波信号相位调制分量补偿,实现ISAR成像的自聚焦。仿真实验表明,该算法可以准确估计回波信号高阶相位参数,提高ISAR成像质量。     

改进的分段多项式建模的电离层相位去污染新方法

时变电离层的相位污染使天波超视距雷达(OTHR)的回波多普勒谱展宽.近年来已发展了基于分段的相位多项式参数建模和高阶模糊函数的方法估计和校正电离层的相位污染.由于实际电离层信道为时变的且不可预测,因此,采用预先确定阶数的建模方法有较大的局限性.本文提出了一种改进的方法来选择相位多项式建模的阶数.该方法引入三个判决准则对分段后的信号作建模阶数的自适应选择.实验结果表明,改进后的算法比原有的分段相位多项式参数估计方法以及其他两种电离层校正方法具有更好的性能,特别在校正快速变化的电离层相位污染时具有更为明显的优势.     

一种新的机载SAR回波高阶多项式相位误差提取方法

当载机在SAR回波方位子孔径时间内运动较复杂时,二次相位误差模型不能准确描述载机运动造成的相位误差。针对此情况,该文借鉴PACE算法的思想,提出了一种提取SAR回波中时域高阶多项式相位误差的TPACE算法。TPACE算法将图像对比度函数作为目标函数,以时域高阶多项式相位误差模型系数作为自变量,通过最优化方法提取时域误差系数。文中详细推导了对比度函数关于误差模型系数的梯度表达式,分析了TPACE与以往提取时域高阶多项式相位误差的算法计算量之差别。实际超宽带SAR回波数据处理结果表明,TPACE能有效提取时域高阶多项式误差,是一种计算量相对较小的SAR自聚焦算法。     

短程宽带FMCW雷达信号非线性校正方法研究

调频连续波（Frequency Modulated Continuous Wave,FMCW）合成孔径雷达（Synthetic Aperture Radar,SAR）具有重量轻、截获概率低、高分辨率成像等优点,但其发展受到限制的一个重要因素是发射信号中存在非线性误差。本文针对一部X波段4.8GHz带宽短程调频连续波成像雷达系统中非线性误差较大的问题,提出了一种基于高阶模糊函数（High-order Ambiguity Function ,HAF)和重采样的非线性误差校正方法。该方法结合压控振荡器( Voltage Controlled Oscillator,VCO)的频率电压特性将非线性差频信号拟合为多项式相位信号（Polynomial Phase Signals,PPS）,利用HAF对多项式相位系数进行估计,并利用插值完成非线性误差校正。仿真和实测数据处理结果表明,该方法能准确有效地校正FMCW系统中的非线性误差,且工程适用性强。      

Region-based fractal image compression using heuristic search

Presents work carried out on fractal (or attractor) image compression. The approach relies on the assumption that image redundancy can be efficiently exploited through self-transformability. The algorithms described utilize a novel region-based partition of the image that greatly increases the compression ratios achieved over traditional block-based partitionings. Due to the large search spaces involved, heuristic algorithms are used to construct these region-based transformations. Results for three different heuristic algorithms are given. The results show that the region-based system achieves almost double the compression ratio of the simple block-based system at a similar decompressed image quality. For the Lena image, compression ratios of 41:1 can be achieved at a PSNR of 26.56 dB.     

多通道有源噪声控制算法的仿真研究

由于FXLMS算法结构简单、性能稳定和具有全局收敛的特点,在各种自适应有源噪声控制领域中,多采用FXLMS算法及其改进形式。着重讨论了3种多通道有源噪声控制算法,对3种算法收敛性进行了比较,并利用实际采集的车内噪声对算法性能进行了验证。仿真结果表明3种多通道算法能有效地降低车内的低频段噪声。     

Low-complexity data reusing methods in adaptive filtering

Most adaptive filtering algorithms couple performance with complexity. Over the last 15 years, a class of algorithms, termed "affine projection" algorithms, have given system designers the capability to tradeoff performance with complexity. By changing parameters and the size/scale of data used to update the coefficients of an adaptive filter but without fundamentally changing the algorithm structure, a system designer can radically change the performance of the adaptive algorithm. This paper discusses low-complexity data reusing algorithms that are closely related to affine projection algorithms. This paper presents various low-complexity and highly flexible schemes for improving convergence rates of adaptive algorithms that utilize data reusing strategies. All of these schemes are unified by a row projection framework in existence for more than 65 years. This framework leads to the classification of all data reusing and affine projection methods for adaptive filtering into two categories: the Kaczmarz and Cimmino methods. Simulation and convergence analysis results are presented for these methods under a number of conditions. They are compared in terms of convergence rate performance and computational complexity.     

A unified algorithm of reliability estimation of k-out-of-n systems implied by the structure function

A new algebraic form of the structure function of a system will be proposed and its significant properties will be proved. The usefulness of these results in construction of algorithms of reliability estimation will be presented.The general approach to the desig of the algorithms of reliability estimation for both k-out-of-n and consecutive k-out-of-n systems will be presented. The method of the estimation of the lower and/or upper bound of system failure rate will be also discussed.The appropriate program in PASCAL will be given.     

信息隐藏与检测算法的特性分析

本文从系统模型的角度研究了信息隐藏与检测的问题,提出了用参数估计理论来衡量信息提取算法的优劣.同时,用信息隐藏中常用的两种算法和四种应用环境为例,推导了参数估计的方差下限,并且用仿真结果验证了理论结果,同时得到了对应的信息提取算法为最佳估计算法的结论.     

Standard and quasi-standard stochastic power control algorithms

In an energy-efficient wireless communication system, transmit powers are minimized subject to predetermined signal-to-interference ratio (SIR) requirements. In this paper, a general framework for distributed stochastic power control (PC) algorithms is proposed, where the transmit powers are updated based on stochastic approximations. The proposed algorithms are distributed in the sense that no global information is needed in the power updates. Interference to each user is estimated locally via noisy observations. Two types of stochastic PC algorithms are studied: standard stochastic PC algorithms where the interference estimator is unbiased, and quasi-standard stochastic PC algorithms where the interference estimator is biased. The conditions under which the stochastic PC algorithms converge to the unique optimal solution are identified. Corresponding to two classes of iteration step-size sequences, two types of convergence, the probability one convergence and convergence in probability, are shown for both algorithms based on recent results in the stochastic approximation literature. Based on the theoretical results, some well-known stochastic PC algorithms, such as stochastic PC with matched filter receivers, and joint stochastic PC with blind minimum mean-squared error (MMSE) interference suppression, are revisited; several new stochastic PC algorithms, such as stochastic PC with minimum-power base-station assignment, and stochastic PC with limited diversity, are proposed. It is shown that these algorithms fall into either the standard or the quasi-standard stochastic PC framework. Simulation results are given to illustrate the performance of the proposed algorithms in practical systems.     

Asynchronous control algorithms for increasing the efficiency ofthree-stage connecting networks for multipoint services

A study is made of the problem of designing low complexity control algorithms for controlling three-stage connecting networks with the objective of improving system performance. The chosen approach is based on the theory of connecting networks and makes use of rearrangement algorithms. These algorithms are applicable to a number of environments, including multipoint connections, time plan modifications in satellite systems, and real-time routing. The main feature of the algorithms is an asynchronous mode of operation for modifying the system switching configurations. A theoretical framework has been developed for defining the conditions that must hold for the asynchronous rearrangements to work. A quantitative evaluation of these algorithms obtained with a computer simulation program is given     

Generalized threshold chase algorithms

 Three generalized threshold Chase algorithms called GTC Ⅰ,GTC Ⅱ and STC are proposed in this paper.They are the combination of the generalized minimum distance(GMD)decoding algorithm with the Chase algorithm.Although the decoding error probabilities of these algorithms are very close to that of the Chase algorithm,the decoding speeds are faster,especially at higher signal-to-noise ratio(SNR),hence they are of greater practical value.The results of computer simulations are given,showing the advantages of these algorithms.     

Statistical Performance of MUSIC-Like Algorithms in Resolving Noncircular Sources

This paper addresses the resolution of the conventional and noncircular MUSIC algorithms for arbitrary circular and noncircular second-order distributions of two uncorrelated closely spaced transmitters observed by an arbitrary array. An explicit closed-form expression of the mean null spectrum of the conventional and noncircular MUSIC algorithms is derived using an analysis based on perturbations of the noise projector instead of those of the eigenvectors. Based on these results, theoretical and approximate interpretable closed-form expressions of the threshold array signal-to-noise ratios (ASNR) at which these two algorithms are able to resolve two closely spaced transmitters along the Cox and the Sharman and Durrani criteria are given. It is proved that the threshold ASNRs given by the conventional MUSIC algorithm do not depend on the distribution of the sources including their noncircularity, in contrast to the noncircular MUSIC algorithm for which they are very sensitive to the noncircularity phase separation of the sources. This threshold ASNR given by the noncircular MUSIC algorithm is proven to be comfortably lower than that given by the conventional MUSIC algorithm except for weak phase separations of the sources for which the resolving powers of these two algorithms are very close. Finally, these results are analyzed through several illustrations and Monte Carlo simulations.      

沉底及掩埋弹性小目标主动检测系统设计

随着数学理论和信号处理理论的不断发展,主动声呐检测方法也愈加丰富,但在主动声呐检测问题中,由于混响的存在使经典信号处理方法的应用受到限制。设计了一套用于集成各种算法的主动声呐检测系统,介绍了整体框架的实现和几个抗混响算法,演示了一些基于实际数据的初步结果。