共查询到17条相似文献,搜索用时 125 毫秒
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线性调频信号参数快速估计 总被引:1,自引:0,他引:1
线性调频(LFM)信号参数检测是对SAR对抗的一个重要问题,本文在对用Radon—Wigner变换、快速解线调和最大似然(ML)估计和分析LFM信号的基础上,给出一种消除ML估计带来旁瓣的方法,进一步提出了一种局部快速搜索的最大似然估计法,并用于LFM信号的起始频率和调频斜率等参数的估计。最后给出了三种快速算法的计算机模拟结果。 相似文献
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线性调频参数估计方法的数学统一 总被引:2,自引:0,他引:2
本文给出了连续复线性调频(LFM)信号Radon-Wigner变换(RWT)、Wigner-Hough变换(WHT)、分数阶傅立叶变换(FrFT)、解线调方法(Dechirp)和最大似然(ML)方法的相互转换关系.给出了参数估计的最佳表述及其离散形式,省略包含调频率的表达式系数,将RWT、WHT、FrFT和Dechirp和ML方法用统一表达式表述.几种方法的离散LFM信号参数估计均可以用ML或去斜方法实现,并采用FFT方法提高运算速度,因此最佳快速算法的计算量和估计性能是相同的.本文对于这几种参数估计方法的快速算法和估计性能研究具有指导意义. 相似文献
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给出了一种提高HF雷达距离分辨的信号处理方法.首先用参数模型来描述雷达探测信号,然后用最大似然(ML)法对模型参数进行估计.最后给出仿真实验结果. 相似文献
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部分样本雷达信号的参数估计 总被引:1,自引:0,他引:1
线性调频信号参数检测是SAR对抗的一个重要问题 ,其估计参数的方法有多种 ,但对于分析部分样本LFM信号而言 ,绝大多数估计方法的误差很大。在用快速相关解线调估计和分析部分样本LFM信号存有误差的基础上 ,提出了一种改进的快速相关解线调算法运用于部分样本LFM信号的起始频率和调频斜率参数的估计 ,减小了误差。最后对改进的算法进行了仿真 ,证实了改进后的有效性。 相似文献
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Joint estimation of symbol timing and carrier frequency offset of OFDM signals over fast time-varying multipath channels 总被引:2,自引:0,他引:2
In this paper, we present a novel joint algorithm to estimate the symbol timing and carrier frequency offsets of wireless orthogonal frequency division multiplexing (OFDM) signals. To jointly estimate synchronization parameters using the maximum likelihood (ML) criterion, researchers have derived conventional models only from additive white Gaussian noise (AWGN) or single-path fading channels. We develop a general ML estimation algorithm that can accurately calculate symbol timing and carrier frequency offsets over a fast time-varying multipath channel. To reduce overall estimation complexity, the proposed scheme consists of two estimation stages: coarse and fine synchronizations. A low complexity coarse synchronization based on the least-squares (LS) method can rapidly estimate the rough symbol timing and carrier frequency offsets over a fast time-varying multipath channel. The subsequent ML fine synchronization can then obtain accurate final results based on the previous coarse synchronization. Simulations demonstrate that the coarse-to-fine method provides a good tradeoff between estimation accuracy and computational complexity. 相似文献
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This paper considers the problem of maximum likelihood (ML) estimation for reduced-rank linear regression equations with noise of arbitrary covariance. The rank-reduced matrix of regression coefficients is parameterized as the product of two full-rank factor matrices. This parameterization is essentially constraint free, but it is not unique, which renders the associated ML estimation problem rather nonstandard. Nevertheless, the problem turns out to be tractable, and the following results are obtained. An explicit expression is derived for the ML estimate of the regression matrix in terms of the data covariances and their eigenelements. Furthermore, a detailed analysis of the statistical properties of the ML parameter estimate is performed. Additionally, a generalized likelihood ratio test (GLRT) is proposed for estimating the rank of the regression matrix. The paper also presents the results of some simulation exercises, which lend empirical support to the theoretical findings 相似文献
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信道估计是无线通信系统必须加以解决的关键技术之一,采用导频符号辅助的方法进行信道估计是目前各类无线通信系统常用的方法。本文针对平衰落信道提出了最大似然(ML)算法和最大后验概率(MAP)估计算法,给出了ML估计和MAP估计之间的关系,仿真了MAP估计和ML估计的方差与导频符号长度的关系,提出当导频符号长度的取值超过20个符号长度时,MAP信道估计明显优于ML信道估计。 相似文献
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Maximum Likelihood Localization of a Diffusive Point Source Using Binary Observations 总被引:1,自引:0,他引:1
Saravanan Vijayakumaran Yoav Levinbook Tan F. Wong 《Signal Processing, IEEE Transactions on》2007,55(2):665-676
In this paper, we investigate the problem of localization of a diffusive point source of gas based on binary observations provided by a distributed chemical sensor network. We motivate the use of the maximum likelihood (ML) estimator for this scenario by proving that it is consistent and asymptotically efficient, when the density of the sensors becomes infinite. We utilize two different estimation approaches, ML estimation based on all the observations (i.e., batch processing) and approximate ML estimation using only new observations and the previous estimate (i.e., real time processing). The performance of these estimators is compared with theoretical bounds and is shown to achieve excellent performance, even with a finite number of sensors 相似文献
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Tomas McKelvey 《Circuits, Systems, and Signal Processing》2002,21(1):39-55
Methods for estimating linear dynamical models from frequency data are studied, including the properties of frequency domain data generated by the discrete Fourier transform. The stochastic characteristics of the frequency domain data lead to a maximum likelihood (ML) formulation of the frequency domain estimation problem. Both discretetime and continuous time models are discussed. Consistency and variance of the ML estimate are described, and the connection with simpler frequency domain estimation schemes as well as the time domain ML method is pointed out.Supported by the Swedish Foundation for International Cooperation in Research and Higher Education (STINT). This work was partly completed while the author was visiting the Department of Electrical and Computer Engineering, University of Newcastle, Australia. 相似文献