Signal-to-noise ratio comparison of angular signal radiography and phase stepping method

Grating-based x-ray phase contrast imaging has the potential to be applied in future medical applications as it is compatible with both laboratory and synchrotron source. However, information retrieval methods are important because acquisition speed, scanning mode, image quality, and radiation dose depend on them. Phase-stepping （PS） is a widely used method to retrieve information, while angular signal radiography （ASR） is a newly established method. In this manuscript, signal-to-noise ratios （SNRs） of ASR are compared with that of PS. Numerical experiments are performed to validate theoretical results. SNRs comparison shows that for refraction and scattering images ASR has higher SNR than PS method, while for absorption image both methods have same SNR. Therefore, our conclusions would have guideline in future preclinical and clinical applications.

Study of signal-to-noise ratio driven by colored noise

This paper investigates the signal-to-noise ratio(SNR)driven by colored noise and weak input signals.Based on the Cauchy-Schwarz and Rayleigh quotients inequalities,an analytical expression of SNR is developed,and its upper band is closely related to the Fisher information of noise.For mimicking the colored noise,we adopt the first-order moving-average model and propose the optimal input signal waveform.The stochastic resonance effect in threshold systems is demonstrated for the Gaussian mixture colored noise.The obtained results will be interesting in the case of improving the nonlinear filter performance by adding noise to the weak signal corrupted by the colored noise.

Long term integration of radar signals with unknown Doppler shift for ubiquitous radar

Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.

A Novel Peak-to-Average Power Ratio Reduction Scheme via Tone Reservation in OFDM Systems

In this paper, a novel signal-to-clipping noise ratio and least squares approximation tone reservation scheme(SCR-LSA TR) is proposed to reduce the peak-to-average power ratio for orthogonal frequency division multiplexing systems. During the SCR procedure, only the element with the maximal amplitude is picked for processing, which not only decreases the algorithm complexity, but also helps to overcome the BER deterioration. With the LSA method, the amplitude of the peak-cancelling signals can approximate to that of the original clipping noise as much as possible. Through the combination of the optimization factor in the LSA method, the classic SCR method can achieve better PAPR reduction with faster convergence. Simulation results show that the proposed SCR-LSA TR scheme has less in-band distortion and smaller out-of-band spectral radiation. The BER of the proposed scheme shows a better performance especially under the 16-QAM over the additive white Gaussian noise channel.

The correlation between stochastic resonance and the average phase-synchronization time of a bistable system driven by colour-correlated noises

This paper investigates the correlation between stochastic resonance （SR） and the average phase-synchronization time which is between the input signal and the output signal in a bistable system driven by colour-correlated noises. The results show that the output signal-to-noise ratio can reach a maximum with the increase of the average phase- synchronization time, which may be helpful for understanding the principle of SR from the point of synchronization; however, SR and the maximum of the average phase-synchronization time appear at different optimal noise level, moreover, the effects on them of additive and multiplicative noise are different.

Micro-Doppler feature extraction of micro-rotor UAV under the background of low SNR

Micro-Doppler feature extraction of unmanned aerial vehicles(UAVs)is important for their identification and classification.Noise and the motion state of the UAV are the main factors that may affect feature extraction and estimation precision of the micro-motion parameters.The spectrum of UAV echoes is reconstructed to strengthen the micro-motion feature and reduce the influence of the noise on the condition of low signal to noise ratio(SNR).Then considering the rotor rate variance of UAV in the complex motion state,the cepstrum method is improved to extract the rotation rate of the UAV,and the blade length can be intensively estimated.The experiment results for the simulation data and measured data show that the reconstruction of the spectrum for the UAV echoes is helpful and the relative mean square root error of the rotating speed and blade length estimated by the proposed method can be improved.However,the computation complexity is higher and the heavier computation burden is required.

Photoelectric detection technology of laser seeker signals

The measurement of the rolling angle of the projectile is one of the key technologies for the terminal correction projectile.To improve the resolution accuracy of the rolling angle in the laser seeker weapon system, the imaging model of the detector, calculation model of the position and the signal-to-noise ratio(SNR) model of the circuit are built to derive both the correlation between the resolution error of the rolling angle and the spot position, and the relation between the position resolution error and the SNR. Then the influence of each parameter on the SNR is analyzed at large,and the parameters of the circuit are determined. Meanwhile, the SNR and noise voltage of the circuit are calculated according to the SNR model and the decay model of the laser energy. Finally,the actual photoelectric detection circuit is built, whose SNR is measured to be up to 53 d B. It can fully meet the requirement of0.5° for the resolution error of the rolling angle, thereby realizing the analysis of critical technology for photoelectric detection of laser seeker signals.

A NOVEL METHOD FOR ESTIMATING THE SNR OF UNKNOWN EMITTER SIGNAL

It is important to estimate the Signal-to-Noise Ratio(SNR) of unknown emitter signal accurately.In order to resolve the disadvantages of present algorithm,a novel method is proposed in this letter.We extract and normalize the information of zero frequency of received signal by the Wigner-Vile Distribution(WVD) transformation and then get the approximate power of original signal by mathematic transformation,at last,we get the estimate value of SNR by the known account formula of SNR.Simulation results show that it is correct and feasible.

Implication of two-coupled tri-stable stochastic resonance in weak signal detection

Stochastic resonance （SR） has been proved to be an effective approach to extract weak signals overwhelmed in noise. However, the detection effect of current SR models is still unsatisfactory. Here, a coupled tri-stable stochastic resonance （CTSSR） model is proposed to further increase the output signal-to-noise ratio （SNR） and improve the detection effect of SR. The effects of parameters a, b, c, and r in the proposed resonance system on the SNR are studied, by which we determine a set of parameters that is relatively optimal to implement a comparison with other classical SR models. Numerical experiment results indicate that this proposed model performs better in weak signal detection applications than the classical ones with merits of higher output SNR and better anti-noise capability.

THE METHOD OF SEPARATING HARMONIC SIGNALS FROM MULTIPLICATIVE AND ADDITIVE NOISES

This paper focuses on the extraction of a harmonic signal from multiplicative and additive noises. A method is proposed in two stages： （1） to square the original discrete time series, which includes both signals and noises, and form a new time series. By this means, the multiplicative noise is converted to additive noise; and （2） to filter out the noise by using existing noise removal schemes. With a large amount of simulation, experimental results demonstrated the efficiency and effectiveness of this newly developed method in terms of Signal-to-Noise Ratio （SNR） and other criteria. Prom the experiment, it is also found that： the two kinds of noises affect the SNR differently. In general, the SNR is not influenced by multiplicative Gaussian noise regardless of its variance. However, if both kinds of noise exist, the SNR decreases with the incensement of the Variance of Additive Noise to Multiplicative Noise Ratio （VAMNR）. This analysis is also supported by simulation work.

New Wavelet Thresholding Algorithm in Dropping Ambient Noise from Underwater Acoustic Signals

Underwater Wireless Communication, largely dependent on the acoustic communication between the machines, is largely affected by various types of noise in the shallow and deep water. However ambient noise which is due to multiple sources (e.g. shipping, wind) and no one source dominates. Ambient noise masks the acoustic signal to a large extent. Hence today it has drawn the attention of the experts to reduce its effect on the received signal. This paper discusses ambient noise problem and devises a new wavelet thresholding method to reduce its effect. Afterwards a comparative study on statistical parameters is shown to prove the efficiency of the devised method.

Parametric SNR Estimation Based on Auto-Regressive Model in AWGN Channels

Signal-to-noise ratio（SNR）estimation for signal which can be modeled by Auto-regressive（AR）process is studied in this paper.First,the conventional frequency domain method is introduced to estimate the SNR for the received signal in additive white Gauss noise（AWGN）channel.Then a parametric SNR estimation algorithm is proposed by taking advantage of the AR model information of the received signal.The simulation results show that the proposed parametric method has better performance than the conventional frequency doma in method in case of AWGN channel.

Network Sorting Algorithm of Multi-Frequency Signal with Adaptive SNR

An signal noise ratio（ SNR） adaptive sorting algorithm using the time-frequency（ TF）sparsity of frequency-hopping（ FH） signal is proposed in this paper. Firstly,the Gabor transformation is used as TF transformation in the system and a sorting model is established under undetermined condition; then the SNR adaptive pivot threshold setting method is used to find the TF single source. The mixed matrix is estimated according to the TF matrix of single source. Lastly,signal sorting is realized through improved subspace projection combined with relative power deviation of source. Theoretical analysis and simulation results showthat this algorithm has good effectiveness and performance.

基于TOPSIS的注塑工艺参数多目标稳健优化设计

针对现有注塑工艺参数稳健设计未安排外表试验以深入分析成型过程中不可控因素的影响、未综合考虑注塑制品的多质量特性等不足,提出基于内外表参数设计、信噪比分析和逼近理想解排序(Technique for order preference by similarity to ideal solution,TOPSIS)的注塑工艺多目标稳健优化设计方法。通过二水平正交试验和方差分析筛选出对注塑制品质量影响最大的主要工艺参数作为可控因素,将其误差作为噪声因素,进行内外表参数设计。利用均匀试验设计和逐步回归分析建立预测给定注塑工艺方案下成型制品质量的二次多项式模型,以快速获得内外表所有试验方案下成型制品的质量指标值,进而高效地计算出内表试验方案下各质量指标所对应的信噪比。在此基础上,利用TOPSIS对内表各试验方案进行优劣排序并选取稳健最优的注塑工艺参数设计方案。手机面板的注塑工艺多目标稳健优化设计实例验证了方法的有效性。

基于相位相干成像的TOFD检测缺陷图像增强处理研究

利用超声衍射时差法(TOFD)对钢制安全壳(CV)焊缝进行缺陷检测时,存在信噪比低和分辨率差等现象。为解决上述问题,发展了一种基于相位相干成像(PCI)的TOFD的图像增强处理算法,该算法适用于平行扫查(B扫查)与非平行扫查(D扫查),针对B扫查和D扫查图像从增强算法原理及其试验效果进行了说明,为后续缺陷定位、定量研究奠定理论基础。首先,利用合成孔径聚焦技术(SAFT)对厚度48 mm的CV试块焊缝中底面开口槽B扫查和D扫查图像进行处理,得到SAFT图像;然后,利用PCI算法对SAFT图像进行相位相干处理。结果表明,PCI算法能够通过减小合成孔径声束宽度有效提高横向分辨率。此外,该算法还能够通过放大相位分布对幅值的作用有效抑制背景噪声,使缺陷信噪比得到提升。并在上述研究基础之上,比较了CCF和SCF权重矩阵增强效果,为实际图像处理中权重矩阵的选择提供参考。

基于自适应估计SNR的分组Turbo码译码算法

针对分组Turbo码自适应Chase译码算法中SNR是预先设定值的情况,提出一种新的自适应估计信噪比(SNR)的译码算法。该方案利用了接收码字的统计信息与SNR之间存在的对应关系来调整门限函数,达到控制译码复杂度的目的。仿真结果表明,所提出的译码算法能自适应反映信道情况,降低译码运算复杂度,提高译码处理速度,获得了较好的性能。

基于SNR比较的协作感知用户选择问题的研究

在实际情况的认知无线电环境下,由于认知用户的感知可靠性存在差异,并不是参与协作的认知用户越多,感知性能越好.综合考虑协作的必要性与协作的增益两方面因素,提出了一种基于信噪比(SNR)比较的协作感知用户选择方案.理论分析及仿真结果一致表明:该方法在有效地提高频谱感知检测性能的同时,减小了参与协作感知的用户数目,提高了协作效率.

LTE-Advanced MIMO低SNR下调制技术性能研究

采用多输入多输出(multiple input multiple output,MIMO)技术来提高无线信道的传输增益,从而提高调制系统中的信噪比、降低调制系统的比特误码率;仿真量化分析了在LTE-Advanced MIMO不同无线场景中,调制系统中信噪比与MIMO技术的天线数,以及调制系统中信噪比与MIMO技术天线的发射功率之间的关系。仿真结果表明,MIMO技术能提高低功率无线场景中调制系统中的信噪比,进而提高调制系统的可靠性。

SNR估计误差对DDEA-Turbo系统的影响

基于数据引导均衡算法(DDEA)的Turbo均衡,求取符号外信息对数似然比(LLR)时需要用到信噪比(或者说噪声方差)信息,在均衡的过程中没法获得准确的信噪比,只能通过估计获得其粗略值。而信噪比的估计误差势必会对均衡的性能产生影响。给出了一种半分析的方法,研究信噪比(SNR)的估计误差对基于DDEA算法的Turbo均衡器性能的影响,相比较于仅靠大量的仿真工作来获取此方面信息的方法来说,该方法省略了很多的仿真工作,而是通过推导的公式计算,所以复杂度降低。通过仿真验证了给出方法的有效性,同时可以看出信噪比过估计对基于DDEA算法的Turbo均衡系统的性能基本不产生什么影响,但是信噪比欠估计会造成误码率的大幅度上升。

深度学习重建算法与单能量对腹主动脉成像质量的参数优选研究

目的比较能谱单能量联合基于模型的自适应统计迭代重建技术(Adaptive Statistical Iterative Reconstruction-V,ASIR-V)与固定100 keV下使用深度学习重组(Deep Learning Image Reconstruction,DLIR)对腹主动脉的图像质量与辐射剂量的影响。方法回顾性收集2022年12月至2023年12月间在齐齐哈尔医学院附属第三医院进行的腹部增强扫描病例。将患者按照所接受的扫描技术分为2组,即常规组(100 keV,DLIR-H)和能谱组(80/140 keV,ASIR-V 40%)。常规组进行DLIR-H、DLIR-M、DLIR-L、ASIR-V 40%、ASIR-V 60%、ASIR-V 80%重建。利用能谱分析软件GSI Volume Viewer将原始数据重建ASIR-V 60%、ASIR-V 80%2个等级,在3个ASIR-V等级上以10 keV为间隔重建40~90 keV的图像,与120 kVp-like混合能量图像共同构成19组图像。比较各组图像的噪声(Standard Deviation,SD)、信噪比(Signal to Noise Ratio,SNR)以及对比度噪声比(Contrast to Noise Ratio,CNR),分析得出最佳单能量组。结果60 keV联合ASIR-V 60%的SD、SNR及CNR与120 kVp-like相比,差异无统计学意义(P>0.05);60 keV联合ASIR-V 60%与常规组相比,SNR、CNR及主观评分的差异均无统计学意义(P>0.05),常规组辐射剂量及SD较低,且差异有统计学意义(P<0.05)。结论100 keV下DLIR-H在满足腹主动脉诊断要求的同时还能降低辐射剂量,相对来说,其为腹主动脉的最优重建算法。而60 keV联合ASIR-V 60%为重建腹主动脉的最佳单能量与重建等级的组合。