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。

低SNR下汉语单音节清晰度测量与可懂度估计

在实验室条件下测量了不同频带范围、不同信噪比条件时的语言清晰度和STI-PA,分析了清晰度,STI-PA与信噪比的关系,并根据单音节清晰度与语言可懂度的关系,估计了在满足一定可懂度条件下的最低信噪比及相应的STI-PA。

软件无线电中ADC孔径抖动对SNR影响的建模与仿真

利用Simulink建立了两种仿真模型验证分析软件无线电中ADC孔径抖动对SNR的影响,模型一采用输入信号的抖动来仿真ADC采样孔径抖动产生的影响,模型二采用时钟源加入高斯噪声的方法较真实地模拟了ADC采样时钟的抖动情况。两种模型的仿真曲线与理论曲线基本吻合,证明了模型的正确性,尤其是模型二建模解决了有抖动的采样脉冲产生和参数计算中信号同步的关键问题,得到了更真实、准确的特性曲线,为深入研究高速高精度ADC的孔径抖动测量、分析和控制提供了一个比较可靠的依据,对系统设计提供了有益帮助。

A fast decoupled ISAR high-resolution imaging method using structural sparse information under low SNR

Inverse synthetic aperture radar (ISAR) image can be represented and reconstructed by sparse recovery (SR) approaches. However, the existing SR algorithms, which are used for ISAR imaging, have suffered from high computational cost and poor imaging quality under a low signal to noise ratio (SNR) condition. This paper proposes a fast decoupled ISAR imaging method by exploiting the inherent structural sparse information of the targets. Firstly, the ISAR imaging problem is decoupled into two sub-problems. One is range direction imaging and the other is azimuth direction focusing. Secondly, an efficient two-stage SR method is proposed to obtain higher resolution range profiles by using jointly sparse information. Finally, the residual linear Bregman iteration via fast Fourier transforms (RLBI-FFT) is proposed to perform the azimuth focusing on low SNR efficiently. Theoretical analysis and simulation results show that the proposed method has better performence to efficiently implement higher-resolution ISAR imaging under the low SNR condition.

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.

Nonsaturation Throughput Enhancement of IEEE 802.11b Distributed Coordination Function for Heterogeneous Traffic under Noisy Environment

In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise ratio （SNR） is low, applying this mechanism in DCF greatly improves the throughput and lowers the channel idle time. This paper presents an analytical model for the performance study of IEEE 802.11 MB-DCF for nonsaturated heterogeneous traffic in the presence of transmission errors. First, we introduce the MB-DCF and compare its performance to IEEE 802.11 DCF with binary exponential backoff （BEB）. The IEEE 802.11 DCF with BEB mechanism suffers from more channel idle time under low SNR. The MB-DCF ensures high throughput and low packet delay by reducing the channel idle time under the low traffic in the network. However, to the best of the authors＇ knowledge, there are no previous works that enhance the performance of the DCF under imperfect wireless channel. We show through analysis that the proposed mechanism greatly outperforms the original IEEE 802.11 DCF in the imperfect channel condition. The effectiveness of physical and link layer parameters on throughput performance is explored. We also present a throughput investigation of the heterogeneous traffic for different radio conditions.

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.

Influence of array elements’ consistency on SNR of hydrophone array

The influence of array element’s consistency on the hydrophone array’s signal-to-noise ratio (SNR) is studied. The consistency of array elements means the outputs of all the array’s elements are the same, that is to say, the outputs have the same phase and amplitude when their inputs are the same. The relationship between the SNR and the correlation coefficient of signal and the relationship between the SNR and the correlation coefficient of noise are given. Hydrophone array’s gain with the output of elements’ inconsistent phase and amplitude is analyzed theoretically. When the signal is single-frequency, the gain expression of two-elements array is deduced. Then the gain is calculated when the phase difference is 10° and the amplitude difference is 3 dB. The theoretical analysis is verified through simulation. The simulation results show the variation rule of array’s SNR when the consistency changes: the array SNR gain is greatly affected by the consistency of the elements’ output and the gain decreases as the consistency decreases and the gain may be negative when the amplitude response becomes worse.

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.

A BLIND SNR ESTIMATOR FOR DIGITAL BANDPASS SIGNALS

A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estimation are derived, and simulations are performed for the commonly used digital bandpass signals, such as MPSK (M=2, 4, 8), MFSK (M=2, 4) and MQAM (M=16, 64, 128, 256) signals. Theoretical analyses and simulation results indicate that the proposed algorithm is ef- fective even when the SNR is below 0dB. Furthermore, the algorithm can provide a blind estimator in that it needs neither the parameters of the received signals, such as the carrier frequency, symbol rate and modulation scheme, nor the synchronization of the system.

Effective DOA Estimation Under Low Signal-to-Noise Ratio Based on Multi-Source Information Meta Fusion

Efficiently performing high-resolution direction of arrival(DOA)estimation under low signal-to-noise ratio(SNR)conditions has always been a challenge task in the literatures.Obvi-ously,in order to address this problem,the key is how to mine or reveal as much DOA related in-formation as possible from the degraded array outputs.However,it is certain that there is no per-fect solution for low SNR DOA estimation designed in the way of winner-takes-all.Therefore,this paper proposes to explore in depth the complementary DOA related information that exists in spa-tial spectrums acquired by different basic DOA estimators.Specifically,these basic spatial spec-trums are employed as the input of multi-source information fusion model.And the multi-source in-formation fusion model is composed of three heterogeneous meta learning machines,namely neural networks(NN),support vector machine(SVM),and random forests(RF).The final meta-spec-trum can be obtained by performing a final decision-making method.Experimental results illus-trate that the proposed information fusion based DOA estimation method can really make full use of the complementary information in the spatial spectrums obtained by different basic DOA estim-ators.Even under low SNR conditions,promising DOA estimation performance can be achieved.

A Blackman-Harris windowed triple-spectrum-line interpolation method for measuring SNR of ADCs

In the practical measurement of signal to noise ratio(SNR)of analog-to-digital converters(ADCs)by using fast Fourier transformation(FFT)method,the non-coherent sampling is inevitable,leading to spectral leakage which in turn affects the calculation accuracy and final measurement results.In this paper,a new method based on the Blackman-Harris windowed triple-spectrum-line interpolation is presented for the measurement of ADCs SNR by FFT.The simulation platform is built based on MATLAB and the behavioral dynamic models of the high-speed ADC products of Analog Devices Inc.(ADI)are simulated.The simulation results show that,even in the case of the maximum non-coherent degree,the SNR error is less than0.23dB and reaches the testing standards provided by ADI,confirming that the proposed method is effective for suppressing the spectral leakage effects and improving the SNR test accuracy.

Influence of signal-to-noise ratio on accuracy of spectral analysis by near infrared spectroscopy

As one of the important indicators of spectrometer,signal-to-noise ratio(SNR)reflects the ability of spectrometer to detect weak signals.To investigate the influence of SNR on the prediction accuracy of spectral analysis,we first introduce the major factors affecting the spectral SNR.Taking green tea as an example,the influence of spectral SNR on the prediction accuracy of the origin identification model is analyzed by experiments.At the same time,the relationship between the spectral SNR and prediction accuracy of spectral analysis model is fitted.Based on this,the common methods for improving the spectral SNR are discussed.The results show that the accuracy of the prediction set model first decreases slowly,then decreases linearly,and finally tends to be flat as the spectral SNR decreases.Through calculation,in order to achieve the prediction accuracy of prediction model reaching 90%and 85%,the spectral SNR is required to be higher than 23.42 dB and 21.16 dB,respectively.The overall results provide certain parameters support for the development of new online analytical spectroscopic instruments,especially for the technical indicators of SNR.

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

SUBSPACE-BASED NOISE VARIANCE AND SNR ESTIMATION FOR MIMO OFDM SYSTEMS

This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The special training sequences with the property of orthogonality and phase shift orthogonality are used in pilot tones to obtain the estimated channel correlation matrix. Partitioning the observation space into a delay subspace and a noise subspace, we achieve the measurement of noise variance and SNR. Simulation results show that the proposed estimator can obtain accurate and real-time measurements of the noise variance and SNR for various multipath fading channels, demonstrating its strong robustness against different channels.

Effect of Peak Power and Pulse Width on Coherent Doppler Wind Lidar’s SNR

The laser device is the core component of coherent Doppler wind lidar.The peak power and pulse width of laser transmitting pulse have important effects on SNR.Based on coherent Doppler wind pulse lidar,the peak power and pulse width influence on SNR is studied on the theoretical derivation and analysis,and the results show that the higher the peak power can realize the greater the signal-to-noise ratio of coherent Doppler wind lidar.But when the peak power is too large,the laser pulse may appear nonlinear phenomenon,which cause the damage of the laser.So,the peak power must be less than the stimulated brillouin scattering power threshold.Increasing the pulse width can make the laser device to output more energy,but it will also make the spatial resolution lower,and the influence of turbulence on SNR will be greater.After a series of simulation analyses,it can be concluded that when the peak power is 650W and the pulse width is 340ns,the SNR of the system can be maximized.In addition,the coherent Doppler wind lidar system is set up to carry out corresponding experimental verification.The experimental results are consistent with the theoretical analysis and simulation,which verifies the correctness of the theoretical analysis and simulation results.It provides theoretical basis and practical ex-perience for the design of laser transmitting pulse in coherent Doppler wind lidar system.

SVM辅助的GPS SNR雪深时间序列反演

研究了GPS干涉反射技术GPS-IR(GPS-Interferometric Reflectometry);在利用GPS卫星SNR信号进行积雪深度探测的基础上构建了支持向量机SVM(Support Vector Machine)辅助的GPS SNR雪深时间序列反演模型;对积雪深度进行时间序列预报和与传统GPS-IR积雪探测模型进行精度对比分析。实验结果显示,相比传统GPS-IR雪深反演模型,SVM辅助的GPS SNR雪深时间序列反演模型的雪深预报结果的精度更高,也更符合实测雪深的变化趋势,可为地面积雪雪深反演提供新方法。