分数阶Fourier域多分量微弱LFM信号的检测

为了提高对多分量微弱LFM信号的检测能力,提出了一种基于分数阶Fourier域非均匀采样理论的信号检测方法。首先提出了一种自适应非均匀采样方法,建立了该方法的模型,得到了非均匀采样LFM信号在分数阶Fourier域的频谱表达式。在此基础上,对多分量非均匀采样LFM信号进行了检测研究。计算机仿真结果表明,同传统的信号检测方法相比,该方法对微弱LFM信号具有较好的检测能力,而且减少了运算量,满足了实时性要求。     

基于小波变换的非均匀采样信号频谱的研究

该文提出基于小波变换的非均匀采样信号频谱的检测方法,给出变换函数关系使得非均匀采样信号满足小波变换的两个基本条件。文中说明了小波的非均匀化过程,从均匀小波得到非均匀小波,以非均匀小波分析非均匀采样信号,得到非均匀采样信号的频谱。文中还说明了非均匀小波变换的抗混叠的原理以及对信号频谱的检测方法,最后给出实验结果。理论和实验表明,非均匀采样信号的小波变换方法是一种行之有效的非均匀采样信号的频率检测方法,使用该方法处理信号可以得到准确的频率估计效果。     

A Nonuniform Sampling Approach to Data Compression

A nonuniform sampling approach to digital encoding of analog sources is proposed. The nonuniform sampler is basically a level crossing detector (LCD) which produces a sample whenever the input to the LCD crosses a threshold level. The information about the source signal is contained in the time intervals between level crossings and in the directions of level crossings. By assigning strings of the 2-tuple "00" to represent the time between level crossings and "01" and "10" to denote the directions of level crossings, the output binary sequence of the nonuniform sampling encoder (NSE) contains a high probability of the 0 symbol, which makes it suitable for further simple run-length encoding (RLE) to attain a "good" overall compression ratio. Introduction of prediction converts the NSE to a nonuniform sampling predictive coding (NSPC) scheme, which, depending on the source, can potentially improve the compression ratio. Results obtained in the encoding of a band-limied Gaussian source and a rasterscanned black and white still image reveal that an NSE/RLE or NSPC/ RLE system exhibits performance superior to that of an adaptive delta modulation system.     

Reconstruction of Nonuniformly Sampled Bandlimited Signals Using a Differentiator–Multiplier Cascade

This paper considers the problem of reconstructing a bandlimited signal from its nonuniform samples. Based on a discrete-time equivalent model for nonuniform sampling, we propose the differentiator–multiplier cascade, a multistage reconstruction system that recovers the uniform samples from the nonuniform samples. Rather than using optimally designed reconstruction filters, the system improves the reconstruction performance by cascading stages of linear-phase finite impulse response (FIR) filters and time-varying multipliers. Because the FIR filters are designed as differentiators, the system works for the general nonuniform sampling case and is not limited to periodic nonuniform sampling. To evaluate the reconstruction performance for a sinusoidal input signal, we derive the signal-to-noise-ratio at the output of each stage for the two-periodic and the general nonuniform sampling case. The main advantage of the system is that once the differentiators have been designed, they are implemented with fixed multipliers, and only some general multipliers have to be adapted when the sampling pattern changes; this reduces implementation costs substantially, especially in an application like time-interleaved analog-to-digital converters (TI-ADCs) where the timing mismatches among the ADCs may change during operation.      

一种抗混叠的非均匀周期采样及其频谱分析方法

非均匀采样可以突破采样定理的限制,但非均匀采样信号的频谱在所有频率段均存在混叠频谱噪声,这些频谱噪声会淹没真实信号中的一些频谱幅度较小的信号,使得非均匀采样无法检测小信号。本文提出一种非均匀周期采样方法,该方法既具有非均匀采样抗混叠的特性,又具有均匀采样的消除混叠频谱噪声的特点。文中详细分析了非均匀采样产生混叠频谱噪声的原因,提出了基于非均匀周期采样的傅里叶变换方法,并给出了实验结果。理论和实验表明,非均匀周期采样方法是一种行之有效的采样方法。     

Sampling theorems for uniform and periodic nonuniform MIMO sampling of multiband signals

We examine a multiple-input multiple-output (MIMO) sampling scheme for a linear time-invariant continuous-time MIMO channel. The input signals are modeled as multiband signals with different spectral supports, and the channel outputs are sampled on either uniform or periodic nonuniform sampling sets, with possibly different but commensurate intervals on the different outputs. This scheme encompasses Papoulis' generalized sampling and several nonuniform sampling schemes as special cases. We derive necessary and sufficient conditions on the channel and the sampling rate that allow stable perfect reconstruction of the inputs or, equivalently, perfect inversion of the channel. From an implementation viewpoint, we note that it is desirable that the reconstruction filters have continuous frequency responses. We derive necessary and sufficient conditions that guarantee this continuity property. The frequency responses of the reconstruction filters are specified as solutions to a system of linear equations. Finally, we demonstrate that perfect reconstruction may be possible, even when the channel outputs are sampled at an average rate that does not allow the reconstruction of any output from its samples alone. In certain instances, this average rate can achieve the recently presented fundamental bounds on MIMO sampling density.     

Nonuniform sampling theorems for random signals in the linear canonical transform domain

Nonuniform sampling can be encountered in various practical processes because of random events or poor timebase. The analysis and applications of the nonuniform sampling for deterministic signals related to the linear canonical transform (LCT) have been well considered and researched, but up to now no papers have been published regarding the various nonuniform sampling theorems for random signals related to the LCT. The aim of this article is to explore the nonuniform sampling and reconstruction of random signals associated with the LCT. First, some special nonuniform sampling models are briefly introduced. Second, based on these models, some reconstruction theorems for random signals from various nonuniform samples associated with the LCT have been derived. Finally, the simulation results are made to prove the accuracy of the sampling theorems. In addition, the latent real practices of the nonuniform sampling for random signals have been also discussed.     

Performance of discrete-time predictors of continuous-timestationary processes

The asymptotic performance of linear predictors of continuous-time stationary processes is studied from observations at n sampling instants on a fixed observation interval. Both optimal and simpler choices of predictor coefficients are considered, using uniform sampling as well as nonuniform sampling tailored to the statistics of the process under prediction. The focus is on stationary processes with rational spectral densities and the asymptotic performance for cases with and without a quadratic-mean derivatives is obtained. The analytical results are supplemented by numerical examples depicting small- and large-sample-size performance     

Optimal sub-Nyquist nonuniform sampling and reconstruction formultiband signals

We study the problem of optimal sub-Nyquist sampling for perfect reconstruction of multiband signals. The signals are assumed to have a known spectral support ℱ that does not tile under translation. Such signals admit perfect reconstruction from periodic nonuniform sampling at rates approaching Landau's (1967) lower bound equal to the measure of ℱ. For signals with sparse ℱ, this rate can be much smaller than the Nyquist rate. Unfortunately the reduced sampling rates afforded by this scheme can be accompanied by increased error sensitivity. In a previous study, we derived bounds on the error due to mismodeling and sample additive noise. Adopting these bounds as performance measures, we consider the problems of optimizing the reconstruction sections of the system, choosing the optimal base sampling rate, and designing the nonuniform sampling pattern. We find that optimizing these parameters can improve system performance significantly. Furthermore, uniform sampling is optimal for signals with ℱ that tiles under translation. For signals with nontiling ℱ, which are not amenable to efficient uniform sampling, the results reveal increased error sensitivities with sub-Nyquist sampling. However, these can be controlled by optimal design, demonstrating the potential for practical multifold reductions in sampling rate     

基于瑞利多径衰落信道的信号包络频谱感知

为提高信号采样值之间的相关性和降低噪声对感知性能的影响,该文提出基于信号包络自相关矩阵的频谱感知算法。首先对采样信号等间隔时长截取,以相邻间隔的采样值计算信号自相关性,并构造出近似自相关矩阵。其次依据矩阵次对角线元素性质构造了统计量。分别计算了该统计量的检测概率分布函数与虚警概率分布函数,分析了频谱感知算法的检测性能,算法优化了信号相关性的计算,降低了噪声对感知性能的影响。最后通过仿真验证了不同参数对检测概率和虚警概率的影响,并提出了进一步提高检测性能的措施。     

基于相位声码器法的音乐信号正弦分量检测

设计和实现一种基于相位声码器的音乐信号正弦分量检测方法,该方法将STFT等效为一组均匀滤波器,将各正弦分量分离,并由各通道输出的相位变化率估计正弦分量的瞬时频率,然后通过寻找STFT通道中心频率与瞬时频率映射的定点进行正弦分量检测;同时,针对原始相位声码器的缺点,设计了一个多采样率、非均匀滤波器组对其进行改进。实验结果表明,该方法具有良好的瞬时频率跟踪性能,可作为音乐信号多音高估计的分析前端。     

Blind velocities mitigation for MIMO GMTI radar with Doppler division multiple access waveforms

Multiple-input multiple-output (MIMO) radar with multiple transmitters and multiple receivers can achieve a larger virtual antenna array and more system degrees of freedom; thus applying it to ground moving target indication (GMTI) radar can improve the performance of GMTI. Doppler division multiple access (DDMA) waveforms are approximately orthogonal providing good minimum detectable velocity (MDV) performance. However, in such DDMA systems, a sufficient pulse repetition frequency (PRF) design freedom is required. Furthermore, these waveforms suffer from blind velocities which are serious problems, especially in radar systems with high carrier frequency or low PRF. This paper analyses the blind velocities problem and show that blind velocities are relative to variation of the PRF and/or the carrier frequency. Variable PRF techniques are widely used in conventional GMTI radar including multiple PRFs and variable pulse repetition intervals (PRI). Combined with the characteristics of the DDMA MIMO GMTI radar, this paper proposed two methods to mitigate blind velocities: “multi-PRF DDMA” which employs multiple PRFs over successive coherent processing intervals, and “PRI-dithered DDMA” which employs nonuniform sampling by dithered PRI in slow time. Simulation results demonstrate that both the methods are effective ways to mitigate blind velocities in DDMA MIMO GMTI radar systems.     

Reconstruction of band-limited periodic nonuniformly sampled signals through multirate filter banks

A band-limited signal can be recovered from its periodic nonuniformly spaced samples provided the average sampling rate is at least the Nyquist rate. A multirate filter bank structure is used to both model this nonuniform sampling (through the analysis bank) and reconstruct a uniformly sampled sequence (through the synthesis bank). Several techniques for modeling the nonuniform sampling are presented for various cases of sampling. Conditions on the filter bank structure are used to accurately reconstruct uniform samples of the input signal at the Nyquist rate. Several examples and simulation results are presented, with emphasis on forms of nonuniform sampling that may be useful in mixed-signal integrated circuits.     

Sampling of Bandlimited Signals in Fractional Fourier Transform Domain

Fractional Fourier transformed bandlimited signals are shown to form a reproducing kernel Hilbert space. Basic properties of the kernel function are applied to the study of a sampling problem in the fractional Fourier transform (FRFT) domain. An orthogonal sampling basis for the class of bandlimited signals in the FRFT domain is then given. A nonuniform sampling theorem for bandlimited signals in the FRFT domain is also presented. Numerical experiments are given to demonstrate the effectiveness of the proposed nonuniform sampling theorem.     

A Method to Reconstruct Nth-Order Periodically Nonuniform Sampled Signals

A continuous time signal x(t) with Fouriertransform X(v) band-limited to ?ω /2相似文献   

Corrections for nonuniform sampling distortions in magnetic resonance imagery

A technique for estimating and correcting nonuniform sampling distortions in magnetic resonance imagery is presented. The technique consists of first estimating the sampling grid distortion using a parametric model, and then estimating the uniformly sampled data by interpolation on the nonuniform grid. Parameterized models for two particular sampling grid distortion are presented. Maximum likelihood and maximum a posteriori estimators are developed for these distortions. Using computer simulated data, these estimators are shown to perform well.     

A generalization of nonuniform bandpass sampling

Nth-order nonuniform sampling is described for generalized bandpass signal frequency position, bandwidth, sampling rate, frequency-shift and phase-shift. A bandpass extension to the Nyquist criterion is derived, showing that restrictions on bandpass frequency position for odd orders of nonuniform sampling tend to zero as N tends to infinity. Bandpass interpolants based on the sinc function are derived for the generalized Nth-order sampled bandpass signals. It is shown that, for minimum (Nyquist) rate sampling, these interpolants are comprised of N bandpass filters, each with independent phase. The number of bandpass filters comprising the interpolant is found to decrease as the sample rate increases. The advantage of describing Nth-order sampling as the Nth replication and uniform sampling of a signal is demonstrated. Finally, digital implementation of the Nth-order bandpass sampling interpolants is discussed. It is established that it is not practicable to attempt to perform nonuniform bandpass sampling at the theoretical minimum rate, where the interpolation is to be performed digitally     

Recovery of signals from nonuniform samples using iterative methods

An iterative method to recover a bandlimited signal from its ideal nonuniform samples is proposed. The convergence of iterations is proved, and general regions for convergence are found. It is shown that the iterative method is also applicable to other forms of nonuniform sampling, i.e. natural sampling and interpolated sampling (such as sample-and-hold signal). Simulation results show that this method works effectively and fairly fast, and the errors after a few iterations are negligible if a particular sufficient condition is satisfied or the sampling rate is higher than the Nyquist rate     

Multiple-input multiple-output sampling: necessary density conditions

We consider the problem of multiple-input multiple-output (MIMO) sampling of multiband signals. In this problem, a set of input signals is passed through a MIMO channel modeled as a known linear time-invariant system. The inputs are modeled as multiband signals whose spectral supports are sets of finite measure and the channel outputs are sampled on nonuniform sampling sets. The aim is to reconstruct the inputs from the output samples. This sampling scheme is quite general and it encompasses various others including Papoulis' generalized sampling and nonuniform sampling as special cases. We introduce notions of joint upper and lower densities for collections of sampling sets and then derive necessary conditions on these densities for stable sampling and consistent reconstruction of the channel inputs from the sampled outputs. These results generalize classical density results for stable sampling and interpolation due to Landau.     

Performance bounds for polynomial phase parameter estimation withnonuniform and random sampling schemes

Estimating the parameters of a cisoid with an unknown amplitude and polynomial phase using uniformly spaced samples can result in ambiguous estimates due to Nyquist sampling limitations. It has been shown previously that nonuniform sampling has the advantage of unambiguous estimates beyond the Nyquist frequency; however, the effect of sampling on the Cramer-Rao bounds is not well known. This paper first derives the maximum likelihood estimators and Cramer-Rao bounds for the parameters with known, arbitrary sampling times. It then outlines two methods for incorporating random sampling times into the lower variance bounds, describing one in detail. It is then shown that for a signal with additive white Gaussian noise the bounds for the estimation with nonuniform sampling tend toward those of uniform sampling. Thus, nonuniform sampling overcomes the ambiguity problems of uniform sampling without incurring the penalty of an increased variance in parameter estimation