基于正负分频信号的测速与测距方法

本文针对LFM信号时频耦合、无法准确测速和测距的问题,提出一种基于正负分频信号的高精度测速测距方法。首先,根据信号的频域分割性把它分成正、负LFM信号并分别脉压和检测;其次,计算检测点的特征向量并作目标匹配,精确算出配准目标的速度和距离;最后,用Clean算法实现多目标匹配和参数测量。仿真结果验证了本文方法的有效性和精确性。

频率估计的一种多段分频等长信号融合算法

在低信噪比、被测频率持续时间短的情况下,为提高频率估计精度并适用于多段分频等长信号,本文提出一种分频等长融合算法.因各段信号的被测频率不等,故生成频域分析参数矩阵以实现同频化效果;因同频化后各段信号之间仍然相位不连续,故设计相位差补偿因子矩阵以达到相位连续信号的效果;生成搜索频率序列并得到具有特定形式的功率谱矩阵.为验证算法的正确性,给出了详细的数学证明.仿真表明本文算法适用于任意类型的多段分频等长信号,抗噪性好,频率估计精度比现有方法有较大提高.

基于多段分频等长信号融合的频率估计方法

多段采样信号十分常见,对其进行信息融合能有效提高信号处理的精度,尤其适用于低信噪比、被测频率持续时间短的情况。为提高多段采样信号频率估计的精度和扩展已有方法的适用范围,给出一种多段分频等长信号融合方法。在该方法中,因各段信号的被测频率不等,故生成频域分析参数矩阵以实现同频化效果;因同频化后各段信号之间仍然相位不连续,故设计相位差补偿因子矩阵以达到相位连续信号的效果;因相位差补偿因子矩阵包含未知参数,故生成搜索频率序列以用于实际计算并得到具有特定形式的功率谱矩阵。为验证方法的正确性,给出了数学证明。针对多种应用环境状态进行了仿真实验,结果表明该方法具有普适性,抗噪性好,频率估计精度比现有方法有较大提高。

基于小波消噪的EMD模型在GPS振动信号处理中的应用

经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具有其优缺点,适用于不同的应用。从对GPS振动信号的预处理、时域和频域处理入手,结果分析表明,对GPS振动信号先进行小波滤波消除随机噪声的干扰,再应用经验模式分解更有利于变形特征信息的分离和提取,提取的信号与振动平台记录数据更加吻合。

基于单片机的数字频率计设计

设计了一款基于单片机的数字频率计。电路有信号整形、信号分频、单片机控制及显示模块等部分组成。实现对周期信号的频率测量,测量结果在LCD显示器上显示。测试幅度在0.5V～5V;测试频率在1Hz～1MHz;测量误差≤0.1%。

Fractional S transform-Part 1:Theory

The S transform, which is a time-frequency representation known for its local spectral phase properties in signal processing, uniquely combines elements of wavelet transforms and the short-time Fourier transform （STFT）. The fractional Fourier transform is a tool for non-stationary signal analysis. In this paper, we define the concept of the fractional S transform （FRST） of a signal, based on the idea of the fractional Fourier transform （FRFT） and S transform （ST）, extend the S transform to the time-fractional frequency domain from the time- frequency domain to obtain the inverse transform, and study the FRST mathematical properties. The FRST, which has the advantages of FRFT and ST, can enhance the ST flexibility to process signals. Compared to the S transform, the FRST can effectively improve the signal time- frequency resolution capacity. Simulation results show that the proposed method is effective.

Analyzing Undersampled Signals Using High Order Ambiguity Function Algorithm

Aim To find an effective and fast algorithm to analyze undersampled signals. Methods\ The advantage of high order ambiguity function(HAF) algorithm is that it can analyze polynomial phase signals by phase rank reduction. In this paper, it was first used to analyze the parameters of undersampled signals. When some conditions are satisfied, the problem of frequency confusion can be solved. Results and Conclusion\ As an example, we analyze undersampled linear frequency modulated signal. The simulation results verify the effectiveness of HAF algorithm. Compared with time frequency distribution, HAF algorithm reduces computation burden to a great extent, needs weak boundary conditions and doesn't have boundary effect.

Application of sparse time-frequency decomposition to seismic data

The Gabor and S transforms are frequently used in time-frequency decomposition methods. Constrained by the uncertainty principle, both transforms produce low-resolution time-frequency decomposition results in the time and frequency domains. To improve the resolution of the time-frequency decomposition results, we use the instantaneous frequency distribution function（IFDF） to express the seismic signal. When the instantaneous frequencies of the nonstationary signal satisfy the requirements of the uncertainty principle, the support of IFDF is just the support of the amplitude ridges in the signal obtained using the short-time Fourier transform. Based on this feature, we propose a new iteration algorithm to achieve the sparse time-frequency decomposition of the signal. The iteration algorithm uses the support of the amplitude ridges of the residual signal obtained with the short-time Fourier transform to update the time-frequency components of the signal. The summation of the updated time-frequency components in each iteration is the result of the sparse timefrequency decomposition. Numerical examples show that the proposed method improves the resolution of the time-frequency decomposition results and the accuracy of the analysis of the nonstationary signal. We also use the proposed method to attenuate the ground roll of field seismic data with good results.

Effects of Gabor transform parameters on signa time-frequency resolution

In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.

高频交流环节AC／AC变频变换系统基准正弦电路研究

首次提出并深入分析研究了一类全数字化技术、与电网电压n倍频或n分频信号同步的基准正弦电路,并给出了关键电路参数设计准则与试验结果,试验结果与理论分析一致。该基准正弦电路具有输出正弦电压与电网电压n倍频或n分频信号同步、THD小、幅值可调但不受电网电压波动的影响、简单实用、价格低廉等优点,在高频交流环节AC/AC变频变换系统和UPS中具有重要应用价值。

Multi-Component Signal Processing for the Short Range Radar

To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.

随机共振于滚动轴承支撑的转子早期碰摩故障中的应用

通过仿真确认随机共振可以提取强干扰下的微弱信号。将之应用到实验测量的滚动轴承支撑转子早期碰摩故障信号的检测,避开了轴承产生的倍频信号对碰摩信号的干扰,成功检测到了转子早期碰摩的分频信号。说明随机共振对于滚动轴承支撑的转子早期碰摩故障是有效果的。

Frequency spectrum analysis on micro-seismic signal of rock bursts induced by dynamic disturbance

Blasting and breaking of hard roof are main inducing causes of rock bursts in coal mines with danger of rock burst,and it is important to find out the frequency spectrum distribution laws of these dynamic stress waves and rock burst waves for researching the mechanism of rock burst.In this paper,Fourier transform as a micro-seismic signal conversion method of amplitude-time character to amplitude-frequency character is used to analyze the frequency spectrum characters of micro-seismic signal of blasting,hard roof breaking and rock bursts induced by the dynamic disturbance in order to find out the difference and relativity of different signals.The results indicate that blasting and breaking of hard roof are high frequency signals,and the peak values of dominant frequency of the signals are single.However,the results indicate that the rock bursts induced by the dynamic disturbance are low frequency signals,and there are two obvious peak values in the amplitude-frequency curve witch shows that the signals of rock bursts are superposition of low frequency signals and high frequency signals.The research conclusions prove that dynamic disturbance is necessary condition for rock bursts,and the conclusions provide a new way to research the mechanism of rock bursts.

基于EnDat数据传输周期的多卡同步采集方法

在基于内置传感器的数控机床性能测试中,以三通方式采集EnDat编码器信号与其它类型编码器信号时,存在同步不准的问题,故提出了一种以EnDat信号采集卡为主卡,EnDat数据传输周期分频信号作为采样时钟的多卡同步采集方法。基于CPLD+MCU实现了EnDat数据传输周期的获取及分频电路的设计。通过在数控磨齿机上进行EnDat数据传输周期获取实验,验证了EnDat数据传输周期获取方法及分频电路设计的正确性,并在该数控磨齿机的传动链测试实验中验证了基于EnDat数据传输周期的多卡同步采集方法的可行性。

Continuous frequency and phase spectrograms: a study of their 2D and 3D capabilities and application to musical signal analysis

A new lighting and enlargement on phase spectrogram （PS） and frequency spectrogram （FS） is presented in this paper. These representations result from the coupling of power spectrogram and short time Fourier transform （STFT）. The main contribution is the construction of the 3D phase spectrogram （3DPS） and the 3D frequency spectrogram （3DFS）. These new tools allow such specific test signals as small slope linear chirp, phase jump case of musical signal analysis is reported. The main objective is to and small frequency jump to be analyzed. An application detect small frequency and phase variations in order to characterize each type of sound attack without losing the amplitude information given by power spectrogram

FAST SYMBOL-LEVEL SYNCHRONIZATION FOR TR-UWB SIGNALS USING DOUBLE HYBRID DS-TH SPREADING

A Transmitted Reference (TR) Ultra WideBand (UWB) signal with double hybrid Direct Sequence and Time Hopping (DS-TH) spreading is proposed and its symbol-level synchronization scheme is designed and analyzed. The proposed signaling format can significantly reduce the search space while reducing the spectral lines and eliminating inter-frame interference and multi-user inter- ference. Detailed analysis of the proposed scheme is carried out. Synchronization performance of the proposed signaling format in multipath channel is derived and supported by computer simulation. The search step which is closely associated with the delay of data modulated pulses is analyzed. Using the TH code, the proposed signaling format and synchronization scheme especially works well in moderate and low data rate systems.

Study of seismic spectrum decomposition based on CEEMD

Empirical mode decomposition( EMD) is a powerful tool of time-frequency analysis. EMD decomposes a signal into a series of sub-signals,called Intrinsic mode functions( IMFs). Each IMF contains different frequency components which can deal with the nonlinear and non-stationary of signal. Complete ensemble empirical mode decomposition( CEEMD) is an improved algorithm,which can provide an accurate reconstruction of the original signal and better spectral separation of the modes. The authors studied the decomposition result of a synthetic signal obtained from EMD and CEEMD. The result shows that the CEEMD has suitability in spectrum decomposition time-frequency analysis. Compared with traditional methods,a higher time-frequency resolution is obtained through verifying the method on both synthetic and real data.

Independent Component Analysis Based Blind Adaptive Interference Reduction and Symbol Recovery for OFDM Systems

To overcome the inter-carrier interference （ICI） of orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis （ICA）. Taking into account statistical independence of subcarriers＇ signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation （BSS） framework. In this paper, the ICA- based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.

A quantitative analysis method for GPR signals based on optimal biorthogonal wavelet

Due to the disturbances arising from the coherence of reflected waves and from echo noise,problems such as limitations,instability and poor accuracy exist with the current quantitative analysis methods.According to the intrinsic features of GPR signals and wavelet time–frequency analysis,an optimal wavelet basis named GPR3.3 wavelet is constructed via an improved biorthogonal wavelet construction method to quantitatively analyse the GPR signal.A new quantitative analysis method based on the biorthogonal wavelet(the QAGBW method)is proposed and applied in the analysis of analogue and measured signals.The results show that compared with the Bayesian frequency-domain blind deconvolution and with existing wavelet bases,the QAGBW method based on optimal wavelet can limit the disturbance from factors such as the coherence of reflected waves and echo noise,improve the quantitative analytical precision of the GPR signal,and match the minimum thickness for quantitative analysis with the vertical resolution of GPR detection.

Dynamics of Meandering Spiral Waves Driven by Two-Point Feedback

We numerically study the dynamics of meandering spiral waves in the excitable system subjected to a feedback signal coming from two measuring points located on a straight line together with the initial spiral core. The core location and size radius of the final attractors are computed, and they change with the position of the moving measuring point in a unique way. By the Fourier Spectral analysis, we find the frequency-locked behaviors different from the driving scheme of the external periodic force. It when the moving measuring point approaches closely is also found that the meandering spiral wave can be eliminated the boundary and its feedback gain is large enough. This offers an effective and convenient method for eliminating meandering spiral waves.