The concise fractional Fourier transform and its application in detection and parameter estimation of the linear frequency-modulated signal

A concise fractional Fourier transform （CFRFT） is proposed to detect the linear frequency-modulated （LFM） signal with low signal to noise ratio （SNR）. The frequency axis in time-frequency plane of the CFRFT is rotated to get the spectrum of the signal in different an- gles using chirp multiplication and Fourier transform （FT）. For LFM signal which distributes as a straight line in time-frequency plane, the CFRFT can gather the energy in the corresponding angle as a peak and improve the detection SNR, thus the LFM signal of low SNR can be de- tected. Meanwhile, the location of the peak value relates to the parameters of the LFM signal. Numerical simulations and experimental results show that, the proposed method can be used to efficiently detect the LFM signal masked by noise and to estimate the signal＇s parameters accurately. Compared with the conventional fractional Fourier transform （FRFT）, the CFRFT reduces the transform complexity and improves the real-time detection performance of LFM signal.

A TECHNIQUE FOR MEASURING THE LINEARITY OF A LINEARLY FREQUENCY-MODULATED SIGNAL

A technique for measuring the linearity of a linearly frequency-modulated continuous wave (LFM-CW) signal is presented. It uses a delay-line and a mixer to sense the slope of the output of a sweep oscillator, so that the original form of frequency function deviated from idealized linear slope is retrieved by means of spectrum analysis. Consequently,the linearity of the LFM signal is determined. The formulation is performed based on the principle that an angle-modulated signal can be approximated by an amplitude-modulated signal if the modulation coefficient is sufficiently small. To examine the validity of the procedure and to study the effect of each parameter on the accuracy of measurement, a number of computer simulations has been made. The results of simulation show that the error of the measurement is less than 2%.

Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

Impact of correlated private signals on continuous-time insider trading

A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.

Low-complexity signal detection for massive MIMO systems via trace iterative method

Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.

Early detection of sudden cardiac death by using classical linear techniques and time-frequency methods on electrocardiogram signals

Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.

WIDELY LINEAR RLS CONSTANT MODULUS ALGORITHM FOR COMPLEX-VALUED NONCIRCULAR SIGNALS

Based on the constant modulus criterion, a new Widely Linear(WL) blind equalizer and a novel widely linear recursive least square constant modulus algorithm are proposed to improve the blind equalization performance for complex-valued noncircular signals. The new algorithm takes advantage of the WL filtering theory by taking full use of second-order statistical information of the complex-valued noncircular signals. Therefore, the weight vector contains the complete second-order information of the real and imaginary parts to decrease the residual inter-symbol interference effectively. Theoretical analysis and simulation results show that the proposed scheme can significantly improve the equalization performance for complex-valued noncircular signals compared with traditional blind equalization algorithms.

Effect of inertial mass on a linear system driven by dichotomous noise and a periodic signal

A linear system driven by dichotomous noise and a periodic signal is investigated in the underdamped case. The exact expressions of output signal amplitude and signal-to-noise ratio （SNR） of the system are derived. By means of numerical calculation, the results indicate that （i） at some fixed noise intensities, the output signal amplitude with inertial mass exhibits the structure of a single peak and single valley, or even two peaks if the dichotomous noise is asymmetric; （ii） in the case of asymmetric dichotomous noise, the inertial mass can cause non-monotonic behaviour of the output signal amplitude with respect to noise intensity; （iii） the curve of SNR versus inertial mass displays a maximum in the case of asymmetric dichotomous noise, i.e., a resonance-like phenomenon, while it decreases monotonically in the case of symmetric dichotomous noise; （iv） if the noise is symmetric, the inertial mass can induce stochastic resonance in the system.

Parameter estimation of LFM signals based on time reversal

In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).

Safety Performance Functions for Traffic Signals:Phasing and Geometry

A significant proportion of urban crashes,especially serious and fatal crashes,occur at traffic signals.Many of the black-spots in both Australia and New Zealand cities occur at high volume and/or high-speed traffic signals.Given this,crash reduction studies often focus on the major signalised intersections.However,there is limited information that links the phasing configuration,degree of saturation and overall cycle time to crashes.While a number of analysis tools are available for assessing the efficiency of intersections,there are very few tools that can assist engineers in assessing the safety effects of intersection upgrades and new intersections.Safety performance functions have been developed to help quantify the safety impact of various traffic signal phasing configurations and level of intersection congestion at low and high-speed traffic signals in New Zealand and Australia.Data from 238 signalised intersection sites in Auckland,Wellington,Christchurch,Hamilton,Dunedin and Melbourne was used to develop crash prediction models for key crash-causing movements at traffic signals.Different variables(road features)effect each crash type.The models indicate that the safety of intersections can be improved by longer cycle times and longer lost inter-green times,especially all-red time,using fully protected right turns and by extending the length of right turn bays.The exception is at intersections with lots of pedestrians where shorter cycle times are preferred as pedestrian crashes increase with longer wait times.A number of factors have a negative impact on safety including,free left turns,more approach lanes,intersection arms operating near or over capacity in peak periods and higher speed limits.

GNSS线极化天线干涉信号反演土壤湿度算法测试

利用全球导航卫星系统干涉信号(GNSS-IR)测量土壤湿度已成为热门的研究课题。搭载低成本线性极化天线的智能手机可以方便快捷采集干涉信号信噪比(SNR)。分别仿真垂直和水平线性极化天线采集的GNSS干涉信号,给出2种极化方式下干涉信号SNR波形和反射率随卫星高度角变化的结果。对于垂直极化分量,电磁波会在入射角65°~85°左右时发生全透射,导致干涉信号振荡效果消失,而水平极化不存在该现象。同时,分别仿真右旋圆极化(RHCP)直射和左旋圆极化(LHCP)反射天线采集的GNSS信号,并计算直反射信号的幅值比。在仿真基础上分别利用不同极化天线进行实验,结果表明:采用线性极化天线采集的GNSS干涉信号振荡效果几乎不受卫星高度角的限制,可以为土壤湿度反演提供更多的有效数据,并且反演得到的土壤湿度与同位数据具有良好的一致性,两者的相关性达到0.95。使用搭载圆极化天线的双通道接收机采集北斗系统卫星数据进行对比,相关性达到0.91。对于不同的设备,智能手机采集的GNSS数据占用空间相对比于双通道接收机降低1%,且反演结果相关性接近,由于干涉信号提取直反射信号需要一定的振荡周期,故反演结果的时间分辨率要低于双通道接收机。

SAR抗转发式干扰波形设计与优化

为提高合成孔径雷达(synthetic aperture radar,SAR)系统对抗转发式欺骗干扰的性能,提出一种基于非线性调频(non-linear frequency modulation,NLFM)信号的正交波形设计与优化技术,结合自主收发策略来优化波形组,使捷变发射的波形相互正交,从而达到在复杂环境下抑制转发式欺骗干扰的效果。首先,分析SAR系统转发式欺骗干扰的机理、波形捷变发射方法的合理性和有效性,提出利用正交波形设计进行抗干扰的方法;其次,采用S曲线法和分段函数法产生NLFM信号,基于拉格朗日算法,结合遗传算法对NLFM信号的波形组进行了优化设计;最后,通过仿真实验验证了本文方法设计的优化波形组在SAR系统中对抗转发式欺骗干扰的有效性。结果表明:由分段函数法产生NLFM波形后,在合适的干扰转发时延下,采用拉格朗日遗传算法优化NLFM波形的正交性,改善了波形的主瓣宽度和峰值旁瓣比,增强了捷变波形的正交性,提高了波形质量。

试验环境水下声信号的特征提取方法

水下试验环境参数的反演是水声学研究领域的重要内容。而当前研究的关键是通过对水下声信号做特征提取从而获取参数信息。针对特征提取较难、模型很难拟合等问题。本文提出了一种试验环境水下声信号的特征提取方法。将水下声信号同时用梅尔频谱倒谱系数及线性预测系数处理,两者运用特征加权组合方法得到新的特征矩阵;再应用映射插值算法对特征矩阵进行处理,获得适应神经网络输入的三通道矩阵。本文选取的网络模型为残差神经网络。利用实验室所录制的对河口水库数据集测试表明,本文提出的特征提取方法普遍优于仅利用梅尔频谱倒谱系数或线性预测系数的特征处理方法。利用单频矩形脉冲信号对环境进行深度5分类,准确率平均提升2%。利用线性调频信号对环境进行深度5分类,准确率平均提升2.03%。本文提出的特征提取方法对线性调频信号在深度分类任务下处理的结果要优于单频矩形脉冲信号处理的结果。

基于STM32的智能航行系统设计

为解决航行器智能确定航向并航行的问题,本文采取模块化的思想设计了一款基于STM32的红外导引的智能航行控制系统。该智能航行系统利用红外接收模块进行红外导引信号的接收,采取线性加权法进行航向与导引信号之间的偏离角确定,利用比例-积分-微分(proportion-integration-differentiation,PID)控制算法对控制舵机转角的脉冲宽度调制(pulse width modulation,PWM)信号的占空比进行确定,从而对螺旋桨的转速与舵桨的转角进行可靠控制。根据水池测试结果,该智能航行控制系统能够对红外接收信号进行快速处理,在保持较高航速的条件下进行可靠的航行控制。

面向高速移动环境的二级信号检测算法

正交时间序列复用(OTSM)可以以更低的复杂度实现类似正交时频空间(OTFS)调制的传输性能,为未来需要低复杂度收发器的高速移动性通信系统提供一种有前景的解决方法。针对现有的基于时域的高斯-赛德尔(GS)迭代均衡效率不高的问题,提出二级信号检测算法。首先在时域进行低复杂度线性最小均方误差(LMMSE)检测,其次采用连续超松弛(SOR)迭代算法进一步消除残余符号干扰。为进一步提高收敛效率和检测性能,对SOR算法进行线性优化得到改进SOR(ISOR)算法。仿真实验结果表明,与SOR算法相比,ISOR算法在增加较低复杂度前提下可以提升检测性能并加快算法收敛。与GS迭代算法相比,ISOR算法采用16QAM调制且误码率为10-4时有1.61 dB的增益。

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

低成本接收阵列方向图测试系统与方法

采用传统的相控阵测试方法对数字阵列及数字波束合成进行测试,存在系统复杂、设备齐套周期长、问题难解耦等弊端。因此,对于数字阵列及相关算法,需要一种不依赖天线和物理环境,且能够以低成本和高效率,在系统开发中期完成相关性能评估和迭代的方法。给出一种基于阵列信号模拟技术的低成本接收阵列方向图测试系统,并提出了随机虚拟相移技术用于解决测试精度不足的问题。基于简要的理论分析、给出了测试平台构成和测试流程,并通过仿真和实测验证了方法的有效性。

基于FRFT的低信噪比LFM信号参数快速估计算法

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系,由估计误差推算角度差值,有效降低了运算量,不需要调频斜率正负的先验信息,改进的对数搜索算法可以进一步提高参数估计结果的稳定性和可靠性。仿真结果表明,信噪比在-8 dB以上时该方法在高效率的前提下仍具有良好的参数估计性能,平均估计误差在1%以内,估计结果接近Cramer-Rao下限,满足工程实时处理需求。

Using a linear array to estimate the velocity of underwater moving targets

A new method uses a linear array that takes advantage of underwater physical sound fields to estimate the velocity of an underwater moving target. The mathematical model was established by considering the geometric relationship between the moving target installed with only two transducers to radiate sound of different frequencies and the linear array. In addition, deterministic maximum likelihood and signal phase matching algorithms were introduced to effectively find the directions of arrival （DOAs） of the sound sources of the two transducers installed on the target. Factors causing velocity measurement errors were considered. To track the target, a linear array with a compass, a pressure transducer, a signal conditioner and a digital recorder was configured. Relevant requirements for the array parameters were derived. The simulation showed that a 16-element array with an aperture of less than lm can measure velocity with relative error of no more＇, than 4% when including typical system errors. Anechoic pool and reservoir experiments confirmed these results.

超短基线在低频基阵指向性测量中的应用

随着水声换能器工作频率的降低,实验室空间很难达到自由场和远场测量的要求。而开阔水域的水下环境复杂,基阵很难实现更深层次的吊放,需要安装价格昂贵的吊装平台来获取标准声源与待测基阵之间的相对位姿,效率低且维护成本高。文章采用超短基线定位技术,信号选用线性调频脉冲信号与伪随机编码脉冲信号,并分别基于脉冲压缩法和复相关算法实现距离和相位测量。比对湖上定位精度试验和基阵指向性标定静态试验的结果显示:角度误差为2.5°以内;-6 dB波束宽度在2~10 kHz频率范围内测量误差在5.38%以内。证明超短基线定位在低频基阵指向性标定的可行性。