用于表面等离子体共振的加窗傅里叶变换法信号处理方法

提出了一种采用加窗傅里叶变换的新型信号处理方法，用于提取基于白光光谱干涉相位型表面等离子体共振系统中的相位信息。首先，详尽阐述了这种提取相位信息算法的基本原理；其次，分析了算法中影响精度的几项主要参数，如窗口宽度、采样频率、阈值等，分析表明，只有选取恰当的参数才能得到理想的探测精度；最后，根据实际算取的光谱相位差值得出实际探测精度为3.89410-7 RIU（折射率单位）。与之相对应的理论探测精度为3.90510-7 RIU。理论精度和实验精度误差为0.28%。可以看出，这种算法具有很高的精度。另外，这种算法还具有简单、易与其他数值分析方法结合的优点。     

Unified study on characteristic spectrum representation of signals and spectral decomposition for stationary random signals

The unified relationship between the signal characteristic spectrum representation and the spectral decomposition for the stationary random signal was deeply studied. By using the relations among the differential operators, the integral operator and the Green's function of the characteristic differential equation, the inverse relationship between the Hermitian differential operator and the Hermitian integral operator were given, the characteristic differential equation and corresponding characteristic integral equation were demonstrated, and the spectral representations of both Hermitian differential and integral operators and the general spectral representations for both operators were provided. Based on the superposition method of the stochastic simple harmonic vibration and the Hilbert space unitary operator method for the stationary random signal spectral decomposition, the connection and unification on mathematics of the signal characteristic spectral representation and the stationary random signal spectral decomposition are revealed.     

The new multidimensional time/multi-frequency transform for higher order spectral analysis

A new multidimensional time/multi-frequency higher order spectral(HOS) transform is proposed for transient signals with nonlinear polynomial variation of instantaneous frequency: the short time higher order chirp spectra (HOCS) based on the higher order chirp-Fourier transform and time-domain windowing technique. The proposed transform is compared with the classical multi-frequency HOS based on the Fourier transform. It is shown that the proposed transform is more effective for processing of transient processes in comparison with the classical transform.     

基于信号二次方谱相关特征的MPSK调制识别

针对MPSK信号的调制识别问题,提出了一种新的基于二次方谱相关特征的识别算法。本文对MPSK信号二次方谱相关特性进行了推导和分析,并根据二次方循环谱特性提出了一种新的基于二次谱相关密度的归一化识别特征,新识别特征不受载波相位误差、信号幅度变化的影响,且特征提取方法简单、高效,有利于工程实现。最后对算法识别性能进行了仿真分析,仿真结果表明在低信噪比下该算法具有良好的识别性能,在高斯白噪声环境下,当信噪比为4 dB时,正确识别率可达到95%以上。理论分析和仿真结果都证实了该算法的有效性和可靠性。      

Differences in the power structures of Fourier transform andautoregressive spectral estimates of narrow-band Doppler signals

There is considerable interest in the application of autoregressive (AR) spectral analysis to ultrasonic Doppler signals. Sonograms produced using this technique are, however, very different from those produced using classic Fourier transform methods. Simulations have shown that the heights of the peaks in the AR spectra of narrow-band signals are not necessarily proportional to signal power, and should be used with caution in the context of Doppler signal processing     

Nonparametric algorithm for local frequency estimation of multidimensional signals

Local frequency (LF) estimation of multidimensional (md) signals is considered. The md-Wigner distribution (WD) is used as the LF estimator. The LF is estimated based on the positions of the WD maxima. A nonparametric algorithm for the LF estimation is developed. It is based on the intersection of confidence intervals rule. This algorithm produces an adaptive window size in the WD which gives almost minimal mean squared error of the estimate. A simplified version of this algorithm is developed, with the starting estimate being produced with the WD of one-dimensional signals. Theory is illustrated in examples.     

Frequency estimation of electric signals based on the adaptive short-time Fourier transform

Frequency is an important parameter in the monitoring, control, and protection of power systems and electric equipment. In this article, based on the adaptive short-time Fourier transform, a new digital algorithm is presented to estimate the frequency of electric signals. The novel window, called the Rectangle Self-Convolution Window, is adapted to eliminate the impact of harmonics, and the window length is adjusted according to the variation of signal frequency. The algorithm is easy to implement with high precision and short response time as well as a wide measuring range. It is thus suitable for real-time detection, especially when the frequency changes abruptly and the signal is corrupted by harmonics. Simulation results and practical application show that it is feasible and effective under different conditions.     

基于谱相关的CBOC信号参数盲估计

针对低信噪比下组合二进制偏移载波(CBOC)调制信号的参数盲估计问题,提出了利用谱相关对CBOC信号进行参数估计方法。首先给出了CBOC信号模型,然后根据CBOC信号的数据通道和导频通道之间有良好的正交性特点,详细推导出其谱相关函数可以化简为两个BOC信号谱相关函数的叠加,最后根据CBOC信号循环频率截面的特点进行峰值检索后,实现对伪码速率、载频速率和副载波速率的盲估计。推导结果和计算机仿真分析表明,该方法可以实现在低信噪比下对伪码速率、载频速率和副载波速率的有效估计。     

基于富里哀变换的带限信号外推算法

本文提出一种直接基于富里哀变换的带限信号外推新算法: FFT迭代算法。它在外推性能和谱估值方面比以往的方法好。由于采用了FFT和收敛加速因子,它是一种实用的算法。数值例子表明,对有噪声数据而言,FFT迭代算法是一种有效的外推算法。     

Combining Capon and APES for estimation of spectral lines

We propose combining the Capon and the APES spectral estimators for estimation of both the amplitude and the frequency of spectral lines. The so-obtained estimator does not suffer from Capon's biased amplitude estimates nor from APES' biased frequency estimates or resolution problem. Furthermore, the combined estimator is computationally simpler than APES and has about the same complexity as Capon. Numerical simulations are presented illustrating the increased performance.This work was supported in part by the Swedish Foundation for Strategic Research.     

循环相关熵谱密度估计高效算法研究

针对循环相关熵谱估计循环周期图检测(CPD)算法存在计算效率低、频谱分辨率低和易产生“频谱泄漏”的问题,该文提出一种循环相关熵谱估计的Correntrogram算法。Correntrogram算法借鉴Wigner-Ville 分布(WVD)时频分辨率高的优势,将WVD算法中瞬时自相关函数替换为时变自相关熵函数,即可得到一种循环相关熵谱密度估计算法,称为Correntrogram。首先计算信号的时变自相关熵函数矩阵,再计算时变自相关熵函数矩阵各行的FFT,得到循环自相关熵函数矩阵,最后计算循环自相关熵函数矩阵各列的FFT,得到循环相关熵谱密度。通过仿真调幅信号的处理结果证明：Correntrogram算法有效提高了循环相关熵谱估计效率,避免了“频谱泄漏”,提高了频谱分辨率,该算法程序运行可靠。     

Empirical rules for the selection of parameters for auto-regressive spectral analysis of biomedical rhythms

Auto-regressive modelling provides an attractive method for the accurate estimation of multiple frequency components in short biological time-series comprising only a few cycles of data. The effects of increasing noise content, decreasing number of data points and different relative amplitudes of spectral components on the accuracy of frequency estimation are considered. The relationship between model order, sampling frequency and frequency discrimination between nearly equal components is demonstrated using digit blood-flow data, circadian rhythms and intestinal myoelectrical slow-waves. From these biomedical examples it is concluded that, by choosing parameters carefully, auto-regressive spectral analysis can be considerably superior to standard FFT methods for short time-series analysis.     

Subspace-Based Schemes for NBI and MAI Suppression in DS-CDMA Communications

This paper deals with narrowband interference (NBI) and multiple access interference (MAI) suppression based on subspace-based approaches for direct-sequence code-division multiple-access (DS-CDMA) systems. First, the signal subspace-based and the interference subspace-based techniques are developed to estimate the noisy DS-CDMA signal and the interference signal, respectively. In conjunction with a modified multiple constrained minimum variance multiuser detector, we develop two efficient schemes to deal with the NBI and MAI that do not need any prior knowledge about the characteristics of the interference and specific training sequence. Next, an adaptive implementation based on a signal subspace tracking algorithm and a recursive least mean square algorithm is also developed. Several computer simulation examples in terms of bit error rate are provided for illustrating the effectiveness of the proposed schemes.

Spectral estimation of video signals

Spectrum analyzers are ubiquitous in laboratory work concerning one dimensional signals. This is because linear operators are best examined in the frequency domain. Linear operators, such as linear filters, DCT coders, line shufflers, etc., dominate also the video systems scenario. Their frequency domain study is as appropriate and informative as it is in the case of their one-dimensional counterparts. This paper considers the problems associated with the introduction of two well-known spectral estimation techniques, the periodogram and AR estimates, to the context of television signals. The potential for application of spectral estimation to video problems is exemplified by a number of applications related to the fields of enhanced quality television and HDTV. Special attention is paid to the computational aspects, whose effective solution conditions the practical applicability of the proposed spectral estimation techniques.R. Rinaldo is currently at the Department of Electrical and Computer Engineering of the University of California, Berkeley.     

Wavelet based spectral correlation method for DPSK chip rate estimation

A wavelet-based spectral correlation algorithm to detect and estimate BPSK signal chip rate is proposed. Simulation results show that the proposed method can correctly estimate the BPSK signal chip rate, which may be corrupted by the quadratic characteristics of the spectral correlation function, in a low SNR environment.     

A novel clipping technique for filtering FM signals embedded in intensive noise

A novel adaptive clipping technique for filtering a constant amplitude frequency modulated (FM) signal embedded in non-Gaussian noise is proposed. It is based on the analysis and processing of the estimate of probability density function of a FM signal realization. As a result, modifications of two robust estimators of FM signal amplitude are proposed. It is shown that these estimators can be used for Gaussian and non-Gaussian heavy-tail environments. The proposed clipping technique can exploit one or another obtained robust estimate of the signal amplitude for adaptive setting a threshold. Analysis of signal estimate accuracy for different noise environments is carried out. Comparative analysis of the obtained methods and known approaches based on scanning window nonlinear filtering and optimal robust L-DFT form is performed. It is demonstrated that the usage of clipping-based technique leads to the considerable improvement of the FM signal filtering efficiency in comparison to the aforementioned known approaches for different noise environments and a wide range of input SNR values.     

红外陷阱探测器的光谱辐射定标技术

遥感信息定量化要求高精度的光谱辐射定标技术支撑,使传感器获取数据可比较性、测量精度和长期稳定性得到保证,溯源于低温绝对辐射计的定标技术是发展趋势.为提高红外绝对光谱响应率定标精度,在一种薄膜热电堆传感器上加装镀金反射半球,研制了红外陷阱探测器作为标准传递探测器.利用电替代技术,测试了红外陷阱探测器光谱响应线性、空间响应均匀性和稳定性.通过溯源于低温绝对辐射计的光谱辐射定标系统,标定了其在1. 1~3. 0μm短波红外波段的绝对光谱响应率,合成不确定度小于1%.将红外陷阱探测器应用于红外光谱辐射定标,可缩短低温绝对辐射计的红外光谱功率标准传递链路并提高定标精度.     

Kramer's sampling theorem for multidimensional signals and its relationship with Lagrange-type interpolations

Kramer's sampling theorem, which is a generalization of the Whittaker-Shannon-Kotel'nikov (WSK) sampling theorem, enables one to reconstruct functions that are integral transforms of types other than the Fourier one from their sampled values. In this paper, we generalize Kramer's theorem toN dimensions (N 1) and show how the kernel function and the sampling points in Kramer's theorem can be generated. We then investigate the relationship between this generalization of Kramer's theorem andN-dimensional versions of both the WSK theorem and the Paley-Wiener interpolation theorem for band-limited signals. It is shown that the sampling series associated with this generalization of Kramer's theorem is nothing more than anN-dimensional Lagrange-type interpolation series.This paper was presented at the International Congress of Mathematicians in Kyoto, Japan (1990) and was supported by a CARE Grant #5915 from California Polytechnic State University, San Luis Obispo.     

A prediction model for multipath propagation of pulse signals at VHF and UHF over irregular terrain

A prediction model is presented that permits calculation of the probability of occurrence of distinct multipath propagation of pulse signals at VHF and UHF over irregular terrain. The model applies to terrain characterized by an irregular distribution of obstacles such as hills, buildings, trees, etc., so as to make it impractical to calculate the effect of multipath propagation by diffraction or bistatic-reflection theory. Statistical data on wave propagation over irregular terrain form the basis for the empirical model developed. Generally, the model predicts that 1) for constant transmitter-receiver separation, the amplitudes of the received echoes decrease with increasing echo delay, and 2) for constant echo delay, the occurrence of echo pulses increases as the transmitter-receiver distance increases. The results obtained from the model for rural, hilly terrain, and for a built-up metropolitan area are compared with available measured data.     

RESEARCH ON REAL-TIME CORRECTOR OF SPECTRAL INTERFERENCES

Further advancement of ICP-AES analytical technique is hindered by complex spec-tral interferences.The correction algorithms recently proposed need too much computation andtime to run in real time on general microcomputers.In this paper,a new kind of spectral interfer-ence fast correcting system(SIFCS)was developed,in which the hardware is a TMS32020 digitalsignal processing board in IBM-PC I/O channel and the software is composed of a correctingprogram based on a new effective algorithm and a master program on IBM-PC.Experimentsshow that the processing speed on SIFCS is 50-100 times faster than that on IBM-PC/AT.Thismakes real-time correction of spectral interferences feasible.