Carrier-frequency generation using regular pulse sequences

The formation of simple pulse sequences, by the periodic gating of pulse trains, is considered as a method for generating sets of harmonically related frequencies at increased levels and with some suppression of unwanted harmonics. The method may be used to generate the carrier frequencies for multichannel transmission systems.     

Noise-resistant pulse oximetry using a synthetic reference signal

We describe a noise-resistant pulse oximetry algorithm suited to both signal reconstruction and oxygen saturation estimation. The algorithm first detects relatively clean signal sections from which the heart rate is estimated. The heart rate is used to construct a synthetic reference signal that matches an idealized pulse signal. An adaptive filter continuously processes the sensor signals, reconstructing signals in a linear subspace defined by the reference signal. A projective subspace algorithm is then applied to find the oxygenation level of the blood. We show that under specific circumstances this algorithm solves the sufficiency condition for signal reconstruction in linear saturation estimators. The core principle of using a frequency modulated synthetic reference signal can be applied to adaptive filtering of other physiological signals controlled by the heartbeat, such as blood pressure and electrocardiogram.     

一种基于脉冲样本序列的PRI周期信号分选算法

针对传统脉冲重复间隔(PRI)分选算法在估计PRI方面存在的不足,提出了一种对PRI周期信号的周期进行准确估计的方法。该方法首先从待分选脉冲序列中提取出属于一部雷达的脉冲样本,然后基于这些样本对该雷达脉冲序列的周期进行精确估计,并用估计到的周期值进行脉冲序列抽取从而实现准确分选。相对于传统PRI分选算法,该算法能够在保证周期估计精度的前提下大幅度减少分选过程所需要的时间,从而能够更好地满足信号分选的需求。仿真结果证明了所提算法的有效性。     

On the PAR reduction of OFDM signals using multiple signal representation

Multiple signal representation (MSR) techniques have been used to reduce the high peak-to-average power ratios (PAR) of orthogonal frequency division multiplexing (OFDM) signals. These includes partial transmit sequences (PTS), selected mapping (SLM), selective scrambling and interleaving. All MSR techniques often improve the PAR statistics and are iterative in nature. The PAR reduction obtainable depends on the number of iterations performed, which also increases the complexity of the OFDM transmitter. However, a means to estimate the achievable PAR reduction for a given number of iterations has not been reported in the literature so far. This paper derives a lower bound on the achievable PAR when a MSR technique with a given complexity is used. Our analytical results show a clear asymptotic behavior of the PAR as the number of iterations is increased. Simulation results justify the significance and accuracy of the PAR bound derived.     

稀疏阵列时间反演脉冲信号空间功率合成方法

时间反演电磁波具有时空二维同步聚焦特性.基于时间反演电磁波原理建立了稀疏阵列脉冲信号相干合成的数学模型, 通过理论分析与蒙特卡洛实验相结合的方法研究了合成信号幅度最大时刻目标点合成效率值的统计特征与相位误差及阵元数的关系.分析表明, 在工程实践中, 除尽可能提高相控精度外, 可以通过增加阵列的阵元数来减小目标点合成效率的方差, 以降低相控误差的影响.利用仿真计算研究了相位误差及信号形式对时间反演脉冲信号合成效果的影响, 证实了稀疏阵列时间反演脉冲信号空间功率合成的可行性; 分析方法和结果可以为工程实践中如何折衷需求与条件确定相位误差的控制精度提供理论依据.     

线缆网络中的电磁脉冲传输

电磁拓扑理论在分析电磁干扰(EMI)问题中具有重要的应用价值。本文利用电磁拓扑理论研究了线缆网络的电磁脉冲瞬态响应求解方法,并进行了实验验证。实验利用同轴线建立简单线缆网络,选用方波脉冲作为激励源,先由Fourier变换求得方波脉冲的频谱,根据频域上的BLT超矩阵方程求出线缆网络在方波脉冲作用下各节点的电压,然后再由Fourier逆变换就可求出各节点电压的瞬态响应。通过实验对比说明了此方法的有效性,为进一步研究电磁脉冲在复杂线缆网络中的传输规律打下基础。     

Electromagnetic pulse scattered by a sphere

The magnetic field integral equation for transient electromagnetic scattering by a perfectly conducting sphere is solved by the stepping-in-time procedure. The contributions to the surface current density (SCD) from the self-patch, where the integrand is singular, and from the neighboring patches can be computed by formulas that are more accurate for these patches than the simple product used for other patches. These formulas have to include the time-derivative term of the integrand for the computation of the initial (small) values of the SCD. The improvement in the values of the scattered fields due to these corrections is significant but not dramatic.     

数字化正弦平方脉冲信号

依据正弦平方脉冲的数学方程及其频谱分布，分别导出了与理想和标称视频带宽相对应的正弦平方脉冲的数学表达式及其编程生成方法。实验表明，此法不仅精确，而且便于修改参数，并可直接读人数字电视系统，来测定视频线性响应。     

Advanced acoustic microimaging using sparse signal representation for the evaluation of microelectronic packages

Acoustic microimaging (AMI) has been widely used to nondestructively evaluate microelectronic packages for the presence of internal defects. To detect defects in small devices such as /spl mu/BGA, flip-chip, and chip-scale packages, high acoustic frequencies are required for the conventional AMI systems. The acoustic frequency used in practice, however, is limited by its penetration through materials. In this paper, a novel acoustic microimaging technique, which utilizes nonlinear signal processing techniques to improve the resolution and robustness of conventional AMI, is proposed and investigated. The technique is based on the concept of sparse signal representations in overcomplete time-frequency dictionaries. Simulation and experimental results show its super resolution and high robustness.     

Optimized signal expansions for sparse representation

Traditional signal decompositions such as transforms, filterbanks, and wavelets generate signal expansions using the analysis-synthesis setting: the expansion coefficients are found by taking the inner product of the signal with the corresponding analysis vector. In this paper, we try to free ourselves from the analysis-synthesis paradigm by concentrating on the synthesis or reconstruction part of the signal expansion. Ignoring the analysis issue completely, we construct sets of synthesis vectors, which are denoted waveform dictionaries, for efficient signal representation. Within this framework, we present an algorithm for designing waveform dictionaries that allow sparse representations: the objective is to approximate a training signal using a small number of dictionary vectors. Our algorithm optimizes the dictionary vectors with respect to the average nonlinear approximation error, i.e., the error resulting when keeping a fixed number n of expansion coefficients but not necessarily the first n coefficients. Using signals from a Gaussian, autoregressive process with correlation factor 0.95, it is demonstrated that for established signal expansions like the Karhunen-Loeve transform, the lapped orthogonal transform, and the biorthogonal 7/9 wavelet, it is possible to improve the approximation capabilities by up to 30% by fine tuning of the expansion vectors     

Generating nonorthogonal bases for signal representation

The representation of functions in a basis function expansionz(t)= k=1/=,a _k> x _k (t) is straightforward when the basis functionsx _k (t) are orthogonal. There has been very little work up to this time in determining how to use nonorthogonal bases in signal representation. On the other hand, applications in data compression and signal synthesis often require using specific tailor-made bases. Presented here is a method for constructing very general nonorthogonal bases.Orthogonality has often been used to show that a basis spans the set of functions of interest and to calculate the coefficients of the representation. In this paper, both of these fundamental aspects are addressed for nonorthogonal bases. A new basis {y _k (t)} is obtained by performing a linear transformation on a known existing basis {x _k (t)}. This transformation is constructed such that the coefficients of signal representation on the new basis are readily found. Then, a useful and sufficient condition is placed upon the new basis such that representations converge.The fundamental methods are applied to the standard examples of signal representation. The complex sinusoids, the Rademacher functions, the orthogonal polynomials, and the decaying exponentials are used as the original basis {x _k (t)} from which a new basis {y _k (t)} is generated. Two examples are given to illustrate general applications: one in signal synthesis and one in signal analysis.     

On denoising and best signal representation

We propose a best basis algorithm for signal enhancement in white Gaussian noise. The best basis search is performed in families of orthonormal bases constructed with wavelet packets or local cosine bases. We base our search for the “best” basis on a criterion of minimal reconstruction error of the underlying signal. This approach is intuitively appealing, because the enhanced or estimated signal has an associated measure of performance, namely, the resulting mean-square error. Previous approaches in this framework have focused on obtaining the most “compact” signal representations, which consequently contribute to effective denoising. These approaches, however, do not possess the inherent measure of performance which our algorithm provides. We first propose an estimator of the mean-square error, based on a heuristic argument and subsequently compare the reconstruction performance based upon it to that based on the Stein (1981) unbiased risk estimator. We compare the two proposed estimators by providing both qualitative and quantitative analyses of the bias term. Having two estimators of the mean-square error, we incorporate these cost functions into the search for the “best” basis, and subsequently provide a substantiating example to demonstrate their performance     

Complete Gabor transformation for signal representation

Properties of the Gabor transformation used for image representation are discussed. The properties can be expressed in matrix notation, and the complete Gabor coefficients can be found by multiplying the inverse of the Gabor (1946) matrix and the signal vector. The Gabor matrix can be decomposed into the product of a sparse constant complex matrix and another sparse matrix that depends only on the window function. A fast algorithm is suggested to compute the inverse of the window function matrix, enabling discrete signals to be transformed into generalized nonorthogonal Gabor representations efficiently. A comparison is made between this method and the analytical method. The relation between the window function matrix and the biorthogonal functions is demonstrated. A numerical computation method for the biorthogonal functions is proposed.     

离散信号空间上的最小能量框架在升余弦脉冲信号上的去噪算法

利用离散信号空间上的最小能量(小波)框架对升余弦脉冲信号展开去噪算法的研究。对于所给的2组不同最小能量框架,升余弦脉冲信号和加性高斯白噪声的抽样离散信号在这2组框架的各个子数列下的分解系数将出现明显不同的统计特征。据此给出了2个具体的阈值去噪算法,两者都充分利用了最小能量框架在信号去噪应用上的优点,在保持发送原始信号成分的同时去除了部分噪声成分,获得了较好的处理效果。仿真结果表明,当调制方式为BPSK且升余弦脉冲信号受加性高斯白噪声影响时,如果利用2个算法对接收波形进行去噪预处理,则接收信号的信噪比大幅度提升,在误码率上可以分别获得3.1dB和2.7dB左右的性能增益。     

Blind deconvolution of ultrasound sequences using nonparametric local polynomial estimates of the pulse

The problem of reconstructing the reflectivity of a biological tissue is examined by means of blind deconvolution of the echo ultrasound signals. It is shown that the quality of the reconstruction procedure can be significantly improved when initially the ultrasonic pulse is accurately estimated. A new approach to the estimation of the ultrasound pulse echo sequences is proposed, using local polynomial approximation, which is closely related to the wavelet transform theory. This approach can be viewed as a modification of homomorphic deconvolution, by using bases different from the Fourier basis of the space of square-integrable functions L2. The bases used here are the orthogonal compactly supported wavelet bases. It is shown that the locality of the estimate can be extremely useful in number of cases of practical interest, resulting in estimates with smaller root-mean squared (rms) errors, as compared with estimates employing the Fourier basis. This approach is applied to ultrasound signals, for estimation of the ultrasound pulse log-spectrum from the log-spectrum of radio-frequency (RF) sequences. It is shown, conceptually and experimentally, that the proposed approach can provide robust and rapidly computed estimates of the ultrasound pulses from the RF-sequences, as obtained in the process of tissue scanning. The pulse phase was recovered using the minimum-phase assumption, which was found to hold for the transducers in use. The obtained pulse estimates are used for the deconvolution of the RF-sequences, which result in stable estimates of the tissue reflectivity function, fairly independent of the properties of the imaging system. Simulated data, data obtained from several phantoms and from in vitro experiments have been processed and the results seem to be quite promising.     

Generation of customized ultrahigh repetition rate pulse sequences using superimposed fiber Bragg gratings

We propose and experimentally demonstrate the use of superimposed fiber Bragg gratings (FBGs) as amplitude or phase filtering stages for generating ultrahigh-repetition-rate optical pulse bursts from a single ultrashort pulse. This approach offers the advantages of a compact all-fiber solution and provides high flexibility in tailoring the temporal features of the generated pulse sequence, namely, the repetition rate, as well as the shape and duration of both the individual pulses and the temporal envelope of the burst. To demonstrate the capabilities of the proposed approach, we generate near-flat-topped optical pulse bursts with repetition rates as high as /spl ap/170 GHz at a wavelength of 1.55 /spl mu/m using uniform and linearly chirped superimposed FBGs. We show that superimposed linearly chirped FBGs are more energetically efficient and provide increased design flexibility than superimposed uniform FBGs. Our experimental results also show the robustness of the technique to imperfections in the grating structures and to variations in the input pulse quality.     

Electromagnetic pulse transmission in homogeneous dispersive rock

The effect of the frequency dependence of the conductivity and permittivity of rock for pulse transmission is considered. These high-frequency dispersive effects appear to play a major role in determining the transient response of the medium. A quantitative understanding is achieved by adopting a dispersion model that consists of multiple Debye relaxation processes. It is shown that the results differ significantly from earlier transient calculations that assume frequency independent permittivities and conductivities.     

Algorithm for the nominal resolution in rectangular pulse signal using the ambiguity matrix

It is a main form using the main beamwidth of the ambiguity function to judge the signal resolution,in which the range or Doppler resolution of the signals are investigated for the targets close to each other.However,for the pulse signal with rectangular envelope,if the nominal range resolution is calculated from the classic definition,there exists the problem of infinite integral for the high power terms of sine function,and a definite result could not be obtained.Though a definite solution of the nominal velocity resolution can be calculated from the definition,the calculation for the signal consisting of multiple-pulse,especially several periods,isvery complex.The paper begins with the physical meaning of nominal resolution rather than from the definition formula to solve the problem using the ambiguity matrix,and make the calculation simplified greatly.     

Ambiguity function of periodic pulse shaped sequences

The influence of ideal time-limited pulse shapes and ideal band-limited pulse shapes on the ambiguity function of periodic pulse shaped sequences, which are used in direct sequence spread-spectrum systems and pulse compression applications, is investigated. Furthermore, an upper bound on the absolute values of the sidelobes of the ambiguity function valid for an ideal time-limited pulse shape is derived     

Efficient pulse compressor for Golay complementary sequences

The highly regular structure of binary Golay complementary sequences of length 2/sup N/ makes possible a very simple correlator for these sequences. The algorithm called fast Golay correlation (FGC) performs the correlation of the input radar signal with the Golay sequence using only 2.log/sub 2/(M) operations per input sample as opposed to M operations required by standard correlators. This algorithm is also valid for complex sequences of the same length. This fast correlator and the good autocorrelation properties of Golay sequences make them the ideal choice for high speed, long sequence pulse compression. Sequence agility on the pulse to pulse basis is also possible at the expense of some added complexity.<>