Damped sinusoidal signals parameter estimation in frequency domain

Parameter estimation of noisy damped sinusoidal signals in the frequency domain is presented in this paper. The advantage of the frequency domain approach is having the spectral energy concentrated in frequency domain samples. However, the least squares criterion for frequency estimation using frequency domain samples is nonlinear. A low complexity three-sample estimation algorithm (TSEA) for solving the nonlinear problem is proposed. Using the TSEA for initialization, a frequency domain nonlinear least squares (FD-NLS) estimation algorithm is then proposed. In the case of white Gaussian noise, it yields maximum likelihood estimates, verified by simulation results. A time domain NLS (TD-NLS) estimation algorithm is also proposed for comparison.The Cramer-Rao lower bound (CRLB) of the frequency domain estimation algorithms is derived. The theoretical analysis shows that the FD-NLS can yield a near-optimal performance with few energy-concentrated samples. On the other hand, the TD-NLS does not have the energy concentration property and requires more time domain samples to perform satisfactory estimation. Simulation results verify that the frequency domain estimation algorithms provide better tradeoff between computational complexity and estimation accuracy than time domain algorithms.     

Algorithm for the detection and parameter estimation of multicomponent LFM signals

A novel algorithm based on Radon-Ambiguity Transform (RAT) and Adaptive Signal Decomposition (ASD) is presented for the detection and parameter estimation of multicomponent Linear Frequency Modulated (LFM) signals. The key problem lies in the chirplet estimation.Genetic algorithm is employed to search for the optimization parameter of chirplet. High estimation accuracy can be obtained even at low Signal-to-Noise Ratio(SNR). Finally simulation results are provided to demonstrate the performance of the proposed algorithm.     

Frequency determination of a noisy signal by zero-crossings counting

In many cases, the presence of noise troubles the measurements of signal frequency. Generally the signal to noise ratio is not high enough to neglect the effects of noise on the frequency determination. In this paper, we present a new method, based upon signal processing, which tends to overcome this difficulty. Two points must be emphasized. The first one deals with the great simplicity of the frequency determination by zero crossings counting and the second one with the good accuracy of the results.     

Extended linear regression for undersampled face recognition

Linear Regression Classification (LRC) is a newly-appeared pattern recognition method, which formulates the recognition problem in terms of class-specific linear regression with sufficient training samples per class. In this paper, we extend LRC via intraclass variant dictionary and SVD to undersampled face recognition where there are very few, or even only one, training sample per class. Intraclass variant dictionary is adopted in undersampled situation to represent the possible variation between the training and testing samples. Three types of methods, quasi-inverse, ridge regularization and Singular Value Decomposition (SVD), are designed to solve low-rank problem of data matrix. Then the whole algorithm, named Extended LRC (ELRC), is presented for face recognition via intraclass variant dictionary and SVD. The experimental results on three well-known face databases show that the proposed ELRC has better generalization ability and is more robust to classification than many state-of-the-art methods in undersampled situation.     

修正MUSIC算法对相关信号源的DOA估计性能

本文介绍了用修正ＭＵＳＩＣ算法提高相关信号源ＤＯＡ估计性能的方法。理论分析表明,采用该方法后,可将相关信号源的相关系数平均降低为原来的６３％,因而可改善ＭＵＳＩＣ算法对相关信号源的ＤＯＡ估计性能。且该方法不影响对非相关信号源ＤＯＡ的估计,计算量也无明显增加。计算机仿真实验结果验证了上述理论分析的正确性。     

基于HAF估计的超宽带LFM信号距离像频域校正

为更准确且简洁地表达超宽带的线性调频(LFM)信号的非线性相位,文中采用一种高阶模糊函数,而不是经典的泰勒展开来表达非线性相位多项式,并用高阶模糊函数(HAF)法估计非线性相位多项式系数。针对因目标延时不同导致的非线性程度不同的问题,采用了一种频域校正法补偿回波的非线性相位,一次性完成不同距离目标的一维距离像聚焦,无需对不同距离目标分别进行校正处理,算法效率大大提高。     

采用图像处理的跳频信号参数盲估计

针对短波复杂信道环境下的跳频信号参数估计问题,提出了一种基于图像处理的跳频信号参数盲估计算法。该算法在时频分析的基础上采用灰度共生矩阵提取信号的纹理特征,通过对纹理特征量的分割实现信号与背景噪声的分割,并运用形态学滤波去除二值化后产生的椒盐噪声;然后根据连通区域标记得到的各个信号在时频图中的位置信息来聚类,从而去除定频、突发等干扰信号,分选出跳频信号;最后根据分选出的跳频信号提取其跳频频线并进行修正,估计出跳频信号的跳周期、跳变时刻和跳频频率。仿真实验表明,该算法切实有效,能够在较低的信噪比条件下精确地估计出跳频信号的参数。     

一种新的跳频信号时延估计方法

针对噪声环境下的跳频信号,提出了一种基于稀疏分解的时延估计方法。对跳频信号采用稀疏分解重构进行了研究,在此基础上,在不同天线下对跳频信号分别进行重构,得到每跳信号对应的载波频率和时间中心,从而估计出跳频信号的时延。仿真结果表明,在信噪比大于7 dB时,跳频信号的时延估计误差基本趋近于零,验证了时延估计方法的有效性。     

Adaptive frequency estimation of sinusoidal signals in colored non-Gaussian noises

This paper studies the problem of sinusoidal frequency estimation in colored non-Gaussian ARMA noises. A new adaptive approach is proposed by using the second-and third-order statistics of the measurements. Because of the simultaneous establishment of the signal and noise models, the new approach is applicable for tracking the frequencies at each time instant for stationary and nonstationary signal and/or noise cases. The effectiveness of the new approach is demonstrated by extensive computer simulations. As expected, the approach proposed in this paper outperforms the correlation-based approaches in suppressing the effects of the colored non-Gaussian ARMA noises.     

High-resolution direction finding of non-stationary signals using matching pursuit

One of the main goals of time–frequency (TF) signal representations in non-stationary array processing is to equip multi-antenna receivers with the ability to separate sources in the TF domain prior to direction finding. This permits high-resolution direction-of-arrival (DOA) estimation of individual sources and of more sources than sensors. In this paper, we use linear decomposition of sensor data based on matching pursuit (MP). The leading atoms of the MP, which capture most of the source TF signatures, can be different for different sources and, as such, provide the desired source discrimination. The MP coefficients with high signal-to-noise ratio (SNR) and corresponding to the leading decomposition atoms are used to develop the MP-MUSIC DOA estimation for non-stationary source signals. We demonstrate the source discriminatory capability of the proposed technique using linear FM, nonlinear FM, and other non-stationary signals. Further, we compare MP-MUSIC performance with conventional MUSIC and the time–frequency MUSIC, which incorporates bilinear transforms.     

MSK信号的参数估计

针对通信侦察中MSK信号参数估计的实际应用,提出构造延迟相乘自混频辅助信号获取与原信号同码速率的基带脉冲,对该脉冲采用小波变换提取边沿信息并进行谱分析实现信号码速率的估计;提出采用平方律和一阶循环矩子集相结合,通过检测循环频率位置的方法实现MSK信号的载波估计.这些算法无需MSK信号的任何先验信息,从而有利于通信侦察机...     

一种关于相参脉冲信号频率的最优估计算法

该文针对噪声干扰下的相参脉冲信号的频率估计问题,提出了一种新的最优估计算法：多级频率估计算法,这种算法是一种最优估计算法,并具有正确概率高、计算量小等优点。通过仿真试验验证了算法的可行性、最优性。     

Frequency and Offset Online Estimation of Sinusoidal Signals Based on High-Order Nonlinear Continuous Differentiator

Real-time parameter identification of si-nusoidal signals is an essential research topic due to its broad utilization in both theoretical studies and engineer-ing practice. A tracking differentiator based online estima-tion framework has been proposed to simultaneously iden-tify frequencies and offset of given multi-sinusoidal signal. Tracking differentiator is exploited in presented framework to track the time derivatives of measurements which are then utilized to estimate the frequencies and offset. We introduce a tracking differentiator called high-order non-linear continuous differentiator into the framework, giving birth to a new estimation algorithm. Comparative exper-iments on both single and two sinusoidal signal are sim-ulated, indicating the superiority of proposed method on both convergent speed and estimation accuracy.     

广义稳健的中国剩余定理及其在欠采样率下频率估计中的应用

该文针对传统中国剩余定理在余数有误差时重构整数不稳健性的缺陷,提出了采用一组非互质的模数和相应的有误差的余数估计任意正整数的广义稳健中国剩余定理,给出了详细的定理证明,得出了算法重构整数公式和误差上限表达式。将该定理用于欠采样下信号频率估计,仿真实例验证了所提算法的稳健性和实际工程应用前景。     

Analysis of multicomponent LFM signals by a combined Wigner-Houghtransform

The aim of the paper is the performance evaluation of a method for the analysis of mono- or multicomponent linear-frequency modulation (LFM) signals, based on the Hough transform of the Wigner-Ville distribution of the signals. A closed form expression is found for the signal-to-noise ratio and the parameter estimation accuracy. The overall method, as any nonlinear method, exhibits a threshold effect. Nevertheless, it is shown to be asymptotically efficient and offers a good rejection capability of the cross terms     

基于数据辅助的MPSK信号频域信噪比估计

为在载波频率精确恢复前提高多进制数字相位调制（MPSK）信号在低信噪比下的估计精度,提出了一种数据辅助的MPSK信号频域信噪比估计算法。算法在符号定时恢复和帧同步后提取同步段符号,相关运算后在频域进行信噪比估计。仿真结果表明,算法估计均值无偏,不受载波频率误差的影响,在符号长度为512、信噪比为-10 dB时,均方误差与克拉美罗界只有0.15 dB的偏差,特别适合于接收信号包含载波频率误差且要求低信噪比下具有较高信噪比估计性能的应用。     

Cramer-Rao Bounds for parameter estimation of phase-coding signals

In this paper, Cramer-Rao Bound (CRB) is derived from phase-coding signal with additive white noise, where three important parameters are focused on: carrier frequency, chip width and amplitude. Simplified and close form expressions of CRB are obtained through complicated derivation, and then are applied to evaluate the performance of the cyclic estimator. The results are accurate enough and serve well as benchmark for evaluating the performance of parameter estimation method. Numerical simulations illustrate the accuracy and applicability of the derived CRB.     

基于模糊聚类的常规通信信号自动分选方法

为解决从干扰环境中自动分选出常规通信信号的问题,提出了一种基于模糊聚类的常规通信信号分选方法.该方法首先利用区分度函数确定最优的相关度阈值参数,然后利用模糊聚类算法对利用频域检测和测向得到的测量集进行信号分选,并对分选后的通信信号进行特征参数估计.实验结果表明,该算法能够在不做任何假定的条件下对常规通信信号进行正确分选,并对窄带信号的特征参数进行准确估计.     

低信噪比下对称三角线性调频信号参数估计

低截获概率雷达的广泛应用导致电子侦察系统截获到的雷达信号大多处于低信噪比环境中。针对目前雷达信号参数估计算法在此环境中性能急剧下降,甚至失效的问题,提出一种基于多相滤波器组和高阶累积量联合处理的对称三角线性调频连续波信号参数估计算法。该算法利用多相滤波器组实现信号在频域上的快速均匀划分,对输出的每个子带信号进行三阶累积量对角切片的短时估计,有效抑制了高斯噪声的干扰,并经过包络检波后得到信号完整的时频矩阵,通过对时频图像进行Radon变换得到信号带宽、周期以及调频斜率的估计,频率曲线的提取得到信号起止频率的估计。仿真结果表明:方法在信噪比大于-12dB时的估计正确率较高。     

Unfolding the frequency spectrum for undersampled wideband data

In this letter, we discuss the problem of unfolding the frequency spectrum for undersampled wideband data. The problem is of relevance to state-of-the-art radio frequency measurement systems, which capture repetitive waveform based on a sampling rate that violates the Nyquist constraint. The problem is presented in a compact form by the inclusion of a complex operator called the CN operator. The ease-of-use problem formulation eliminates the ambiguity caused by folded frequency spectra, in particular those with lines standing on multiples of the Nyquist frequency that are captured with erroneous amplitude and phase values.