调频遥测信号载波频率的精确估计

传统调频遥测信号载波频率估计算法对输入信号降采样后直接进行快速傅里叶变换，实现方法虽然简单，但测量精度较差，无法适应高动态、低信噪比等复杂场景。为此，提出了一种调频遥测信号载波频率的精确估计算法。两并联补偿支路先分别采用正、负调频频率对输入信号进行频率预先补偿，低通滤波后完成降采样处理，削弱调频频率的频谱影响；频率搜索状态对采样数据进行载波多普勒变化率的频率补偿，经过快速傅里叶变换、非相干积分和频谱重心搜索完成频率解算，提高载波频率的检测性能。试验与分析表明，所提算法在高动态、低信噪比等复杂场景下可显著提高调频遥测信号载波频率的估测性能。     

滤波与正交基分解在磁性目标检测中的应用

通过对磁性目标磁异常信号时域和频域特性的分析可知,磁异常信号属于低频信号,且在实际磁异常探测中磁性目标信号被噪声淹没,信噪比较低。针对这种情况提出了基于低通滤波与正交基分解的检测方法,先分析数字滤波器特性,设计约束最小二乘FIR滤波器滤除高频噪声,再利用正交基分解检测算法,大幅提升了磁性目标信号的信噪比,从而实现了磁性目标检测。仿真试验表明,该方法可滤除高频噪声,提升信噪比,增强对磁性目标的检测能力     

Heart instantaneous frequency (HIF): an alternative approach to extract heart rate variability

Our study focuses on a new method of estimating the heart rate variability (HRV) which does not require the use of electrocardiogram (ECG) R-wave detection. Contrary to the R-wave detection method which requires a sampling frequency higher than 100 Hz, the one proposed here can be used to calculate the HRV from an ECG signal sampled at a frequency of approximately 5 Hz with a relative mean error of 0.03. This new method is based on extracting the instantaneous fundamental frequency from the ECG. The method could be efficiently used to extract the HRV from an ECG measured for healthy subjects performing an exercise in which the HRV increases linearly with time, and for subjects with respiratory and cardiac problems. The overall error decreased as we low-pass filtered the HRV with lower cut-off frequencies. Moreover, it was shown that the method could be efficiently used to calculate the HRV from blood pressure measurements and to be robust to noise.     

Improved heart rate variability signal analysis from the beat occurrence times according to the IPFM model

The heart rate variability (HRV) is an extended tool to analyze the mechanisms controlling the cardiovascular system. In this paper, the integral pulse frequency modulation model (IPFM) is assumed. It generates the beat occurrence times from a modulating signal. This signal is thought to represent the autonomic nervous system action, mostly studied in its frequency components. Different spectral estimation methods try to infer the modulating signal characteristics from the available beat timing on the electrocardiogram signal. These methods estimate the spectrum through the heart period (HP) or the heart rate (HR) signal. We introduce a new time domain HRV signal, the Heart Timing (HT) signal. We demonstrate that this HT signal, in contrast with the HR or HP, makes it possible to recover an unbiased estimation of the modulating signal spectra. In this estimation we avoid the spurious components and the low-pass filtering effect generated when analyzing HR or HP.     

On Walsh filtering method for decoding of CPM signals

Walsh filtering has been used as a method to reduce receiver complexity in several coding and modulation systems, especially in continuous phase modulation systems. In this paper, we show that its lowpass filtering ability is poor and alias components arising from an adjacent channel can significantly degrade the maximum-likelihood decoding. Instead, a lowpass filtering method is more robust against adjacent channel interference and thus gives less decoding errors than the Walsh filtering method.     

基于ST-FRFT的非合作水声脉冲信号检测方法

为解决非合作条件下水声脉冲信号检测与参数估计的难题,本文提出了一种基于短时分数阶傅里叶变换（ST-FRFT）的检测方法。线性调频（LFM）和单频（CW）脉冲信号是最常见的两种水下声脉冲信号,在非合作条件下,信号参数信息的缺失使得不能直接采用匹配滤波检测方法,傅里叶变换（FT）对CW信号具有良好的检测增益,但对LFM信号检测增益下降,尤其是具有较大调制率的LFM信号。分数阶傅里叶变换（FRFT）对LFM信号具有良好的能量聚集性特点,有利于LFM信号的检测,并且包含了Fourier变换,同样适用于CW信号的检测。为了同时获得接收信号的时域和频域特征,设计了基于短时分数阶傅里叶变换（ST-FRFT）的检测器,可以实现信号参数未知的情况下对LFM和CW信号的截获检测。理论分析了ST-FRFT与STFT方法针对LFM信号和CW信号的检测性能,基于FT的方法对LFM信号的处理增益受到调制率的影响,相对于CW信号增益下降,并且随窗长呈非线性变化,非合作条件下难以获得最佳窗长,而FRFT对LFM信号可以获得近似匹配滤波的处理增益,提高了LFM信号的检测性能。仿真结果和湖试数据处理结果验证了理论分析的正确性与该方法的有效性。      

Time-varying threshold integral pulse frequency modulation

Several methods have been proposed so far for the analysis of the integral pulse frequency modulation (IPFM) model and detecting its corresponding physiological information. Most of these methods rely on the low-pass filtering method to extract the modulating signal of the model. In this paper, we present an entirely new approach based on vector space theory. The new method is developed for a more comprehensive form of the IPFM model, namely the time-varying threshold integral pulse frequency modulation (TVTIPFM) model. The new method decomposes the driving signals of the TVTIPFM model into a series of orthogonal basis functions and constructs a matrix identity through which the input signals can be obtained by a parametric solution. As a particular case, we apply this method to R-R intervals of the SA node to discriminate between its autonomic nervous modulation and the stretch induced effect.     

频率捷变雷达联合模糊C均值抗间歇采样干扰

间歇采样噪声调制转发干扰是一种兼具压制和欺骗特点的新型有源干扰,是目前雷达抗干扰领域的难点之一.为了提高捷变频雷达对抗噪声调制的间歇采样转发干扰(ISRJ)的能力,该文结合ISRJ时域不连续的特点,提出一种基于频率捷变体制雷达联合模糊C均值(FCM)的抗ISRJ方法.首先,该文设计一种脉内频率编码-脉间频率捷变的雷达发...     

Self-adaptive CH4 concentration detection system based on infrared spectrum absorption principle

Considering that the noises resulting from low modulation frequency are serious and cannot be totally eliminated by the classic filters,a novel infrared(IR) gas concentration detection system based on the least square fast transverse filtering(LS-FTF) self-adaptive modern filter structure is proposed.The principle,procedure and simulation on the LS-FTF algorithm are described.The system schematic diagram and key techniques are discussed.The procedures for the ARM7 processor,including LS-FTF and main program,are demonstrated.Comparisons between the experimental results of the detection system using the LS-FTF algorithm and those of the system without using this algorithm are performed.By using the LS-FTF algorithm,the maximum detection error is decreased from 14.3 to 5.4,and also the detection stability increases as the variation range of the relative error becomes much smaller.The proposed LS-FTF self-adaptive denoising method can be of practical value for mid-IR gas detection,especially for weak signal detection.     

基于递归最小二乘算法的时相调制频移滤波方法

针对噪声干扰,利用时相调制信号的谱相关特性,采用非平稳信号处理方法,提出一种基于递归最小二乘算法的时相调制频移滤波方法;同时对具有循环平稳特性的干扰源抑制方法进行了讨论,并分别给出相应的滤波器框图;对采用该滤波器前后的时相调制系统性能进行了仿真与比较。仿真结果表明:与循环相关匹配滤波方法相比,基于最小二乘算法的时相调制频移滤波方法可以有效抑制噪声对时相调制系统的影响,在满足10-5的误码率条件下,系统的功率需求降低约3dB.     

极化自适应滤波算法的新实现

当目标信号与杂波干扰信号在时域、频域和空域的状态特征难以区分时,若两者在极化域可分,则可利用极化信息进行雷达目标检测。由于在强杂波的情况下信干比比较小,而且干扰的极化状态通常是未知的,或随时间或空间是不断变化的,传统的极化滤波算法并不能满足要求。文中针对强杂波环境下,提出了一种极化域新的自适应滤波算法,该方法基于线性约束最小方差(LCMV)准则,采用变极化接收技术,实现对信号的最佳接收,为实现实时处理和自适应快速变化的干扰,推导了一种递推极化滤波算法,为实现实时跟踪提供了一种可能,仿真结果也证明了该方法的有效性。     

三角调频脉冲信号参数测量方法

为精确测量三角调频脉冲信号参数,文中提出了一种联合时域、调制域测量的方法。时域分析时采用统计脉冲信号包络数值的方法估计判决门限,以实现脉冲个数、脉冲宽度等时域参数的测量。基于时域参数测量结果,调制域分析时采用相位差分法得到信号的瞬时频率曲线,进而获得准确的线性度等调制域参数。仿真结果表明,高信噪比下,该方法比现有其他方法运算量少、误差小。     

基于混合结构导频和FFT低通滤波的OFDM信道估计

精确的估计精度、良好的跟踪能力,以及实现简单是信道估计的三个基本要求.本文提出一种混合结构导频的信道估计新方法,采用块状导频和基于FFT低通滤波的LS算法捕捉准确的信道频域响应,利用少数梳状导频和改进的LS算法跟踪信道变化和修正相位噪声.通过仿真证明,该方法估计精度高,频谱利用高,信道跟踪能力强,实现简单,满足了慢衰落信道环境下的应用要求.     

Combining the discrete wavelet transform and mixed-domain filtering

A novel filtering method is proposed that combines the discrete orthogonal wavelet transform (DWT) with the mixed-domain (mixed-D) filtering method. The method uses the DWT to pre- and postprocess those dimensions of the signal that are transformed to the discrete-frequency domain by mixed-D filtering. Using the DWT in this manner provides a controlled mechanism to partition the spectrum of the input signal into subband signals, which then may be selectively filtered during the linear difference equation (LDE) step of the mixed-D algorithm. It is shown that, when the DWT is computed using filters with ideal high- and lowpass frequency responses, the LDE filters used in the mixed-D filtering stage are unchanged by the introduction of the DWT (although the frequency tuple associated with each LDE filter is altered). This indicates that the mixed-D filtering scheme can be easily used in subband coding systems. Results are given for the filtering of a three-dimensional (3-D) linear trajectory signal, representing a common application in video processing.     

基于去斜滤波与稀疏恢复的探干一体化系统直达波抑制技术

探测干扰一体化系统通过波形一体化设计,利用无典型雷达信号特征的干扰信号进行探测,共享波形、频率、时间、孔径等资源,极大提升了系统资源的综合利用率。然而,为实现有效干扰,探测干扰一体化波形在频段上会与对方雷达信号有所重叠,一体化设备探测回波会受到由对方雷达发射信号带来的强直达波影响,造成探测性能的严重恶化。本文考虑探干一体化系统与线性调频雷达对抗的场景,提出了两种直达波抑制算法（去斜频域滤波与稀疏恢复）。在第一种算法中,通过分数阶傅里叶变换（Fractional Fourier Transform,FRFT）估计对方线性调频直达波调频斜率,构造回波去斜函数,将直达波分量变换为点频信号后通过频率滤波进行滤除。在第二种算法中,以去斜滤波方法作为预处理步骤,针对直达波功率强时去斜滤波带来的回波能量损失问题,利用稀疏恢复的方法恢复损失信号,进一步提升了探干一体化系统的探测能力。通过仿真和实测结果验证了算法可行性。     

Model-Based Detection of Heart Rate Turbulence Using Mean Shape Information

A generalized likelihood ratio test (GLRT) statistic is proposed for detection of heart rate turbulence (HRT), where a set of Karhunen–LoÈve basis functions models HRT. The detector structure is based on the extended integral pulse frequency modulation model that accounts for the presence of ectopic beats and HRT. This new test statistic takes a priori information regarding HRT shape into account, whereas our previously presented GLRT detector relied solely on the energy contained in the signal subspace. The spectral relationship between heart rate variability (HRV) and HRT is investigated for the purpose of modeling HRV “noise” present during the turbulence period, the results suggesting that the white noise assumption is feasible to pursue. The performance was studied for both simulated and real data, leading to results which show that the new GLRT detector is superior to the original one as well as to the commonly used parameter turbulence slope (TS) on both types of data. Averaging ten ventricular ectopic beats, the estimated detection probability of the new detector, the previous detector, and TS were found to be 0.83, 0.35, and 0.41, respectively, when the false alarm probability was held fixed at 0.1.      

Image sequence coding using oriented edges

Second generation image coding techniques, which use information about the human visual system to reach high compression ratios, have proven very successful when applied to single images. These methods can also be applied to image sequences. A directional decomposition based sequence coding technique is presented, in which spatial lowpass and highpass components are analyzed and coded separately. A simple law for sharing the available bits between these components is stated and analytically proved by using a minimum cost/resolution optimality criterion. The detection of directional elements is carried out by using both linear and nonlinear (median) filtering. The coding is based on near optimal estimators which retain only the innovation part of information, and is well suited for differential pulse code modulation. The results of applying this method to a typical sequence are shown. The estimated compression ratio is approximately 320 : 1 (0.025 bits per pixel), allowing a transmission rate of about 41 kbit/second. The resulting image quality is reasonably good.     

基于分数阶傅里叶变换的Chirp浅剖精细探测方法

实现弱回波信号检测和高信噪比(SNR)浅剖图像获取是浅剖精细探测的首要任务。该文在分析分数阶傅里叶变换(FrFT)解卷积原理,推导时间量纲化变换公式的基础上,提出一种基于FrFT的浅剖精细探测新方法。该方法通过FrFT解卷积实现分数阶傅里叶域(u域)沉积层冲激响应求解,采用u域加窗滤波技术对带内噪声进行有效抑制,经时间量纲化变换实现高信噪比u域沉积层冲激响应包络信号至时域浅剖包迹的直接变换,得到高质量的浅剖图像。仿真实验和实测数据处理验证了算法的精细探测能力,算法性能优于脉冲压缩和自回归(AR)预测滤波方法。     

一种新的高速多目标快速参数化检测算法

针对线性调频脉冲压缩雷达参数化检测高速多目标时受到距离徙动、多普勒扩散和速度模糊的影响,该文首先采用联合频域变标脉冲压缩处理与吕方法(2011)实现目标信号的相参积累,然后在其基础上采用基于多普勒频率模糊数搜索的方法完成高速多目标的参数化检测.算法所提出的频域变标脉冲压缩处理可同步完成距离维的徙动补偿与多普勒维的模糊数补偿,降低了实现目标参数化检测的计算复杂度,且由于算法采用相参积累方式,在低信噪比下可以进行精确的目标检测和运动参数估计.相参积累算法运算量分析、计算机仿真以及实测数据处理结果验证了该文所提算法的有效性.     

低信噪比S模式应答信号相关检测方法

针对低信噪比条件下S模式应答信号检测概率低、虚警概率高的问题,提出一种基于数据包检测、单脉冲匹配滤波和报头多脉冲检测等三次相关检测的增强识别方法。该方法首先利用数据包相关检测得到数据包位置,从而确定报头脉冲的检测门限;然后利用单脉冲匹配滤波对信号进行降噪处理,确定脉冲位置;最后估计脉冲幅度和噪声功率,利用多脉冲相关检测识别信号报头。通过这三次相关处理,该识别算法可提高S模式应答信号的准确识别率。理论推导了检测概率的数学表达式,通过计算机仿真,在期望虚警概率下,本文方法基本达到了理论检测概率,同时对比了本文方法与传统的直接匹配滤波法、脉冲前沿检测法、基带归一化互相关法的识别性能,验证了本文算法性能的优越性。