Joint Segmentation of Piecewise Constant Autoregressive Processes by Using a Hierarchical Model and a Bayesian Sampling Approach

We propose a joint segmentation algorithm for piecewise constant autoregressive (AR) processes recorded by several independent sensors. The algorithm is based on a hierarchical Bayesian model. Appropriate priors allow us to introduce correlations between the change locations of the observed signals. Numerical problems inherent to Bayesian inference are solved by a Gibbs sampling strategy. The proposed joint segmentation methodology yields improved segmentation results when compared with parallel and independent individual signal segmentations. The initial algorithm is derived for piecewise constant AR processes whose orders are fixed on each segment. However, an extension to models with unknown model orders is also discussed. Theoretical results are illustrated by many simulations conducted with synthetic signals and real arc-tracking and speech signals     

相参短脉冲辐射源双站TDOA/FDOA直接定位算法

当目标辐射源脉冲信号持续时间较短时, FDOA引起的信号脉内相位变化很小,几乎可以忽略,无法实现TDOA和FDOA联合定位。针对上述问题,通过对相参辐射源信号脉冲间相位补偿,提出了一种利用信号的TDOA和FDOA信息的最大似然直接定位算法。考虑采用运动双站对固定目标辐射源定位情况,以确定性未知信号为模型,推导了高斯白噪声背景下相参脉冲信号联合定位的最大似然估计算法,仿真分析验证了该算法可以利用双站实现对短脉冲相参辐射源的TDOA/FDOA定位。此外,还推导了相参脉冲联合定位的CRLB,表明所提算法在常规信噪比下定位精度可以达到CRLB。      

Comparative Performance Evaluation of RF Localization for Wireless Capsule Endoscopy Applications

This paper presents an assessment of the accuracy of cooperative localization of a wireless capsule endoscope (WCE) using radio frequency (RF) signals with particular emphasis on localization inside the small intestine. We derive the Cramer–Rao lower bound (CRLB) for cooperative location estimators using the received signal strength (RSS) or the time of arrival (TOA) of the RF signal. Our derivations are based on a three-dimension human body model, an existing model for RSS propagation from implanted organs to the body surface and a new TOA ranging error model for the effects of non-homogeneity of the human body on TOA of the RF signals. Using models for RSS and TOA errors, we first calculate the 3D CRLB bounds for cooperative localization of the WCE in three major digestive organs in the path of GI tract: the stomach, the small intestine and the large intestine. Then we analyze the performance of localization techniques on a typical path inside the small intestine. Our analysis includes the effects of the number of external sensors, the external sensor array topology, number of WCEs used in cooperation and the random variations in the transmitted power from the capsule.     

基于Gabor变换的超声回波信号时频估计

 在无损检测中,超声回波往往是一个重叠较严重,含有噪声的多回波信号。根据Gabor变换时频分析的特点,该文提出一种基于Gabor变换的超声回波信号时频估计方法。该文建立回波信号与Gabor变换分析窗函数相似度(即距离)模型,通过模型相似度最小化问题转化为求解回波信号Gabor变换系数模的最大值来估计回波信号的传播时间(TOF)和中心频率(CF),最后推导它们的克拉美-罗界(CRLB)以评价算法的性能。Monte Carlo仿真和实验结果表明该文提出的算法,无论对低信噪比的单回波信号或重叠的多回波信号都能达到较高的精度,而且估计的均方误差在高信噪比时,达到CRLB,即使在低信噪比,也接近CRLB。     

MIMO signal separation for FIR channels: a criterion andperformance analysis

Signal separation for a general system of an arbitrary number of signals is investigated. The signal separation research area deals with the problem of separating unknown source signals that are mixed in an unknown way when only these mixtures are available. A criterion, based on second-order statistics, is formulated to be used in estimating the mixing system. This estimate of the mixing system is used in a separation structure with a parameterization that minimizes the number of parameters to be estimated. Formulae for the gradient and Hessian of the criterion are derived. A formula for the lower bound for the variance of the estimated parameters of the mixing matrix is derived. This lower bound is the asymptotic (assuming the number of data samples to be large) Cramer-Rao lower bound (CRLB). The proposed algorithm is tested with simulations and compared with the CRLB     

A new approach to speech segmentation based on the maximum likelihood

Successful speech recognition is highly dependent on appropriate speech segmentation. The poor efficiency of the sequential detection of abrupt changes in the signals with relatively short stationary intervals, as is the case with speech signals, can be improved by the off-line maximum likelihood segmentation algorithm. In this paper the new segmentation algorithm is presented. For the a priori known number of segments, the algorithm determines such signal partitions for which the sum of segment distortion is minimal. The generalized maximum likelihood distortion measure has been introduced, and has proven to be particularly efficient on short signal segments. In the case of an unknown number of segments, its estimate is obtained comparing the reduction of the distortion. The asymptotic properties of the distortion sequence have been analyzed, which led to the definition of the presented segmentation algorithm. The introduced measure can be applied both to the AR and ARMA models. The segmentation algorithm is verified on test signals as well as on the natural speech signal, for which the pitch synchronous framing scheme is applied. The experimental results also include a comparison of the AR and ARMA model-based segmentations. The first results show that ARMA model-based segmentation gives somewhat better results than the AR model algorithm.Research supported in part by the Mathematical Institute of the Serbian Science Academy and Serbian Science Foundation.     

一种新的LFM信号参数估计算法

针对线性调频信号的参数估计问题,提出了一种新的算法.该算法利用计算信号的二次相位函数,得到其能量分布集中于信号的调频率曲线上的结论,因此通过谱峰检测可以获得信号的调频率估计,进而通过解调频技术得到初始频率的估计.分析了该算法的统计特性,计算机仿真结果表明算法计算量小,性能优良,在信噪比较高时,估计精度可接近CRLB界.     

Discrete spectral peak estimation in incoherent backscatterheterodyne lidar. I. Spectral accumulation and the Cramer-Rao lowerbound

The theory of the Cramer-Rao lower bound (CRLB) and maximum-likelihood (ML) estimators is summarized in the context of a heterodyne lidar. Numerical experiments are described that indicate the scaling of this CRLB with parameters such as the signal bandwidth and the level of noise. This CRLB is also compared with the CRLB of a highly idealized noiseless direct detection system using photon counting. It is found that the asymptotic bounds developed in the radar literature for the heterodyne CRLB should not be used as approximations for the correct expression in lidar applications at intermediate signal levels. Moreover, the variance of the ML estimator may be greater or even less than the heterodyne CRLB, depending on the mechanism leading to the departure from the bound     

Blind separation of piecewise stationary non-Gaussian sources

We address independent component analysis (ICA) of piecewise stationary and non-Gaussian signals and propose a novel ICA algorithm called Block EFICA that is based on this generalized model of signals. The method is a further extension of the popular non-Gaussianity-based FastICA algorithm and of its recently optimized variant called EFICA. In contrast to these methods, Block EFICA is developed to effectively exploit varying distribution of signals, thus, also their varying variance in time (nonstationarity) or, more precisely, in time-intervals (piecewise stationarity). In theory, the accuracy of the method asymptotically approaches Cramér–Rao lower bound (CRLB) under common assumptions when variance of the signals is constant. On the other hand, the performance is practically close to the CRLB even when variance of the signals is changing. This is demonstrated by comparing our algorithm with various methods that are asymptotically efficient within ICA models based either on the non-Gaussianity or the nonstationarity. The benefit of our algorithm is demonstrated by examples with real-world audio signals.     

Sequential speech segmentation based on the spectral ARMA transition measure

Sequential segmentation algorithms based on the AR model tend to produce false alarms or to omit the change for sequences that corresponds to the ARMA model. In this paper a new sequential segmentation algorithm based on the ARMA model is presented. The ARMA model is estimated over the relatively short sequence, which has called for the implementation of the estimation algorithm with appropriately initialized starting values. The proposed algorithm adopts the MGLR concept of the sliding reference and test windows, which allow the process of decision making to be separated from the evaluation of the discrimination function. This has enabled the new triangular decision rule to be proposed; this is based on the expected shape of the discrimination function at the time of the model change. Two possible discrimination functions have been suggested. One of them is optimal in the statistical sense; the other has the better asymptotic behavior. Natural speech signal segmentation is also discussed, and an appropriate pitch-synchronous signal prearrangement has been suggested. This not only enhances the segmentation algorithm but also increases its speed, as the time can be increased by a step equal to the pitch period. The segmentation algorithm is verified on test signals as well as on the natural speech signal. The experimental results also include a comparison of the sequential AR and ARMA model-based segmentation.Research supported in part by the Serbian Science Foundation, grant nos. 0403 and 1007.     

时频空域混叠脉冲串辐射源信号直接定位算法

当既定侦察区域存在多个数目未知且信号参数相似的脉冲串辐射源信号时,采用经典的多目标定位算法和直接定位算法(DPD)均无法对多个辐射源信号进行精确定位.该文提出了一种基于位置信息累积的脉冲串直接定位算法(L-DPD).算法采用多个运动侦察站对固定目标辐射源进行信号接收,充分利用脉冲串信号的位置信息并联合各脉冲的时延、频移...     

随机布局多天线信号联合时差估计Cramer-Rao下界

该文针对随机布局多天线信号联合时差估计Cramer-Rao下界（CRLB）开展研究,在深入研究多路联合参数估计和经典时差估计算法的基础上,首先建立信号模型,进而得到频域的联合概率密度函数,然后推导出Fisher信息矩阵和Cramer-Rao下界的解析表达式。最后,对结果进行了讨论分析,并同两路时差估计Cramer-Rao下界进行了对比。结果表明,多天线联合时差估计能够利用各信号的相同信息,有效提升时差估计性能,而且在低信噪比条件下估计性能改善更为明显。此外,可以看到增加天线数目不可能无限降低时差估计Cramer-Rao下界,其受待估时差的两路信号信噪比限制。      

针对机动目标跟踪的雷达发射波形选择

该文首先在交互多模型(Interacting Multiple Model, IMM)算法的框架下,选择常速模型和自适应加速度模型作为状态模型,以应对实际中非合作目标的非机动与机动状态,并将此算法称为自适应IMM算法。然后针对机动目标跟踪时,雷达发射波形的选择需要兼顾测距测速性能与多普勒容忍性的问题,提出将V型调频(V-Linear Frequency Modulated, V-LFM)信号作为发射波形。通过分析多脉冲线性调频信号,V-LFM信号和M序列3种信号对目标距离和速度估计性能的克拉美罗下界(Cramer-Rao Lower Bound, CRLB)与多普勒容忍性表明,V-LFM信号可以在较少多普勒容忍性损失的情况下,有效提升对目标距离和速度的估计精度。仿真结果表明:发射多脉冲V-LFM信号并采用自适应IMM算法,可以明显提高雷达系统的跟踪性能。     

利用DFT和迭代校正的正弦信号频率估计算法

对电磁信号的频率估计广泛应用于通信、雷达、导航和电子对抗等领域。针对正弦信号的频率精确估计,本文提出了一种利用DFT和迭代校正的频率估计算法,并与现有三种基于DFT的频率估计算法进行了性能仿真对比,分析结果表明,新算法的频率估计性能明显优于其他三种算法,可以得到非常逼近CRLB的频率估计值,迭代校正5次时,频率估计的RMSE距离CRLB不到0.07dB,而且没有估计误差平层,算法估计精度高,对频率的取值范围不敏感,性能稳定,迭代校正的复杂度较低,具有很好的应用价值。      

Passive Source Localization Using Time Differences of Arrival and Gain Ratios of Arrival

A source signal will be subject to different amounts of time-delay as well as attenuation when it reaches a number of spatially separated sensors. Both time-delay and attenuation are dependent on the distance between the source and the receivers. This paper performs a fundamental investigation of whether the gain ratios of arrival (GROAs), defined here as the ratio of the received signal amplitudes at the referenced sensor to the other sensors, can be utilized in conjunction with the time differences of arrival (TDOAs) to improve the source localization accuracy. We begin with a Gaussian random signal model and derive the Cramer-Rao lower bound (CRLB) of a source location estimate based on both GROAs and TDOAs. Our conclusion is that the improvement from GROAs increases when the factor c/omega_o increases, where c is the signal propagation speed and omega_o is the signal bandwidth. The paper proceeds to develop an algebraic closed-form solution for the source location using GROAs and TDOAs. The algebraic solution is proved theoretically to reach the CRLB accuracy under the Gaussian data model. Numerical simulations are included to support and corroborate the theoretical developments.     

复杂背景下的最大熵阈值红外目标分割算法

为了有效地分割出实际拍摄中的红外目标信号,提出了一种适用于复杂背景下的最大熵阈值红外目标分割算法;该算法根据图像中信号的相关性,对图像的干扰信号的预处理,随后对所得的图像信号进行熵值的求取;接着根据目标与背景信号的分布特性,对所获得的目标信号与背景信号进行深入提纯处理,最终获得更为理想的红外目标信号。实验结果表明,该算法能够在不同背景下始终保持较好的红外目标分割效果,且具有耗时低、清晰度高的分割优势。     

组合幂调频信号的时频移估计

为了准确估计接收信号的时频移参数和降低估计复杂度,设计了一种组合幂调频(CPFM)信号,该信号由具有时间间隔的正负幂调频(PFM)信号构成,并提出了基于CPFM信号的时频移估计算法.在算法中首先将CPFM信号降阶,然后独立地估计时延和频移,即采用三次相位函数(CPF)估计时延,通过正负PFM相位相消后再估计频移.相比于分数阶傅里叶变换(FRFT)时频移估计算法,所提算法避免了时延估计对频移估计的影响,而且仅需两次一维搜索,降低了计算量.仿真结果表明,该算法能准确地估计CPFM信号的时延和频移,并且频移估计均方误差(MSE)接近克拉美劳下界(CRLB).     

基于Fast-ICA的CDMA信号扩频序列优化盲估计

针对当前基于分段估计非周期长码DS-SS信号扩频序列的方法,本文在分析长码扩频CDMA信号的特点上,提出基于Fast-ICA的盲估计CDMA信号扩频序列的优化分段取值方法,并给出区别于当前分段长度尽量小、以降低信息跳变概率的分段准则.该方法不仅能够适用于同步单、多用户短码DS-SS信号,也适用于单、多用户非周期长码DS-SS信号.同时,文章提出一种接近于实际应用的分段选择,理论分析和仿真结果验证了本文方法的有效性.     

On the computation of an asymptotic bound for estimating autoregressive signals in white noise

The Cramer-Rao lower bound (CRLB) provides a useful reference for evaluating the performance of parameter estimation techniques. This paper considers the problem of estimating the parameters of an autoregressive signal corrupted by white noise. An explicit formula is derived for computing the asymptotic CRLB for the signal and noise parameters. Formulas for the asymptotic CRLB for functions of the signal and noise parameters are also presented. In particular, the center frequency, bandwidth and power of a second order process are considered. Some numerical examples are presented to illustrate the usefulness of these bounds in studying estimation accuracy.     

超宽带雷达生命信号频率检测的Cramer-Rao下界

该文基于脉冲超宽带顺序信号模型和极大似然准则,结合Fisher信息矩阵和Cramer-Rao矩阵不等式,分析了UWB生命信号参数估计的泛化Cramer-Rao下界(CRLB)。根据等效时间采样原理,采用正弦位移函数近似生命微动信号,推导出了修正的UWB生命信号频率检测CRLB公式。仿真结果表明,增大观测时间、发射脉冲带宽以及系统信噪比可提高UWB雷达生命信号频率检测的精度。心跳信号检测比呼吸信号要求更高。