Signal waveform estimation in the presence of uncertainties about the steering vector

We consider the problem of signal waveform estimation using an array of sensors where there exist uncertainties about the steering vector of interest. This problem occurs in many situations, including arrays undergoing deformations, uncalibrated arrays, scattering around the source, etc. In this paper, we assume that some statistical knowledge about the variations of the steering vector is available. Within this framework, two approaches are proposed, depending on whether the signal is assumed to be deterministic or random. In the former case, the maximum likelihood (ML) estimator is derived. It is shown that it amounts to a beamforming-like processing of the observations, and an iterative algorithm is presented to obtain the ML weight vector. For random signals, a Bayesian approach is advocated, and we successively derive an (approximate) minimum mean-square error estimator and maximum a posteriori estimators. Numerical examples are provided to illustrate the performances of the estimators.     

An improved cyclic beamforming method for signal DOA estimation

Modulated signals used in telecommunication are cyclostationary. This property can be exploited to improve the direction of arrival (DOA) estimation performance. In this work, we propose an improved cyclic beamforming algorithm exploiting cyclostationarity. The proposed method exploits the information of both cyclic correlation matrix and cyclic conjugate correlation matrix with different cyclic frequencies. Compared with the existing methods, the simulation results show that proposed method improves substantially the signal selectivity; also it allows an increase in resolution power.     

基于时空极化导向矢量的阵列信号多维参数联合估计

通过对极化敏感阵列的时域采样构造了具有旋转不变结构的矩阵对,该矩阵对分解的特征值与对应特征向量分别是旋转矩阵和阵列的时空导向矢量,利用该导向矢量和旋转矩阵直接得到信号的频率、二维波达方向和极化的联合估计,该多维参数计算方法具有虚拟阵元和较高的估计精度。简述了多维ESPRIT方法的基本原理,其配对方法采用了多个矩阵束具有相同的特征向量,两种方法均利用了的相同信息-矩阵束的特征值和特征向量,仿真实验验证和比较了两种方法的性能。     

Computationally efficient underwater acoustic 2-D source localization with arbitrarily spaced vector hydrophones at unknown locations using the propagator method

This paper presents a propagator-based algorithm for underwater acoustic 2-D direction-of-arrival (DOA) estimation with arbitrarily spaced vector hydrophones at unknown locations. The proposed algorithm requires only linear operations but no eigen-decomposition or singular value decomposition into the signal and noise subspaces. Comparing with its ESPRIT counterpart (Wong and Zoltowski, IEEE J Oceanic Eng 22:566–575, 1997a), the proposed propagator algorithm has its computational complexity reduced by this ratio: the number of sources to quadruple the number of vector hydrophones. Simulation results show that at high and medium signal-to-noise ratio, the proposed propagator algorithm’s estimation accuracy is similar to its ESPRIT counterpart.

Application of natural computing algorithms to maximum likelihood estimation of direction of arrival

This work presents a study of the performance of populational meta-heuristics belonging to the field of natural computing when applied to the problem of direction of arrival (DOA) estimation, as well as an overview of the literature about the use of such techniques in this problem. These heuristics offer a promising alternative to the conventional approaches in DOA estimation, as they search for the global optima of the maximum likelihood (ML) function in a framework characterized by an elegant balance between global exploration and local improvement, which are interesting features in the context of multimodal optimization, to which the ML-DOA estimation problem belongs. Thus, we shall analyze whether these algorithms are capable of implementing the ML estimator, i.e., finding the global optima of the ML function. In this work, we selected three representative natural computing algorithms to perform DOA estimation: differential evolution, clonal selection algorithm, and the particle swarm. Simulation results involving different scenarios confirm that these methods can reach the performance of the ML estimator, regardless of the number of sources and/or their nature. Moreover, the number of points evaluated by such methods is quite inferior to that associated with a grid search, which gives support to their application.     

SIMFA信号用于机载雷达LPI性能分析

提出一种机载LPI(Low Probability of Intercept)雷达HPRF(High Pulse Repetition Frequency)波形,实现了波形设计产生、接收处理,同时对波形抗干扰性能、目标探测性能和LPI性能进行了分析。首先,从原理上对所设计SIMFA(SIMultaneous Frequency Agile)信号的产生方法进行了数学分析,给出波形产生方法;然后,对SIMFA信号的接收及信号处理方法进行研究,实现了单通道接收机对所设计波形的顺利接收;其次,对于电子对抗常用的两种干扰机--瞄准式窄带干扰机和信道化接收机,给出了SIMFA信号的抗干扰性能;再次,分析了SIMFA信号的目标探测性能,并给出提高目标探测性能的方法;最后,通过截获因子的分析,说明了SIMFA信号LPI性能的有效性。     

Two-dimensional DOA estimation of coherent signals using acoustic vector sensor array

In this paper, we present two new methods for estimating two-dimensional (2-D) direction-of-arrival (DOA) of narrowband coherent (or highly correlated) signals using an L-shaped array of acoustic vector sensors. We decorrelate the coherency of the signals and reconstruct the signal subspace using cross-correlation matrix, and then the ESPRIT and propagator methods are applied to estimate the azimuth and elevation angles. The ESPRIT technique is based on the shift invariance property of array geometry and the propagator method is based on partitioning of the cross-correlation matrix. The propagator method is computationally efficient and requires only linear operations. Moreover, it does not require any eigendecomposition or singular-value decomposition as for the ESPRIT method. These two techniques are direct methods which do not require any 2-D iterative search for estimating the azimuth and the elevation angles. Simulation results are presented to demonstrate the performance of the proposed methods.     

低信噪比条件下DS信号的检测和参数估计

本文在对目前存在的各种DS信号检测方法进行充分分析、研究的基础上，提出了一种预处理修正周期的DS检测方法。计算机模拟表明，与其他方法相比，该算法具有较好的检测和参数估计性能。     

矢量信号源中IQ调制器的设计与实现

实现了一种应用于矢量信号源中的新型IQ调制器。其中,硬件电路包括FPGA电路,滤波、放大、输出电路以及控制器电路,软件设计主要有基带信号发生器和基于改进型CORDIC算法的IQ调制。该调制器不但可以直接实现MASK,MFSK,MPSK,QPSK,MSK以及QAM等调制,还可以产生正交载波信号。仿真与实际测试结果证明了该设计的正确性和优越性。     

基于数据矩阵奇异值分解的时—空二维信号处理

本文提出一种利用阵列接收信号数据矩阵奇异值分解的时－空二维信号谱估计方法，该方法对线阵接收信号构成的数据矩阵进行奇异值分解，构造出噪声奇异向量，利用信号空间与噪声空间的正交性获得时－空二维谱，该方法可用于高分辨测向测速系统中，计算机模拟表明了该算法的有效性。     

基于谱估计的噪声调频信号检测方法研究

对干扰信号的频谱特征进行精确测量和分析是实施有效的电子反干扰(ECCM)的重要步骤.通过对噪声调频干扰信号的频谱特征分析,提出采用合适的功率谱估计方法来检测噪声调频信号的主要频谱特征参数.利用MATLAB/Simulink仿真软件分别建立了噪声调频信号源和谱估计方法的系统模型,研究了系统采用不同的谱估计方法和参数设置的情况下所能够达到的检测精度,并根据仿真结果分析比较了不同谱估计方法的性能.     

Maximum a posteriori estimation in presence of film grain noise

Maximum a posteriori (MAP) estimation of images in the presence of film grain noise has been presented. Image statistics have been assumed as gaussian with known mean and variance. Signal independent transformations have been used which considerably reduce the computations in MAP estimation. Normalised mean square error (NMSE) has been evaluated and the results have been discussed.     

Maximum likelihood estimation and MUSIC in array localization signal processing: A review

Algorithms to treat the maximum likelihood (ML) estimation problem in array localization signal processing are reviewed, including the alternating projection method, the iterative quadratic maximum likelihood method and the expectation-maximization method. The relationship of ML estimators and the MUSIC algorithm is presented. The Cramer-Rao bounds for the deterministic and stochastic models in array localization are summarized. Finally, the problem of the estimation of the number of sources is discussed.     

一种修正的线性调频信号参数估计算法

研究了加性噪声中线性调频信号的参数估计问题。基于相位解卷和多项式拟合,考虑到初始相位可能出现模糊,提出了一种修正的线性调频信号参数的联合估计算法。仿真实验证实了所提出的修正算法的有效性。     

一种低信噪比下PSK信号载波频率估计方法

提出了一种利用自适应陷波器对单频信号分量衰减的特性估计PSK信号的载波频率的方法.信号通过陷波器滤波,输出能量最小对应的频点即为信号的载波估计频率.仿真结果表明,在低信噪比环境下该方法的估计误差小于1％.     

Waveform preserving encoders for the compression of EEG data

This paper discusses several approaches to the redundancy reduction of clinical electroencephalographic (EEG) data. The encoders presented here are basically of two types. The first type compresses EEG data with very little visual or spectral information present in the original lost in the compression/decompression process. The other type compresses EEG data with some loss of visual reconstruction quality (although still acceptable) but with the advantage of achieving high compression ratios, and providing a convenient and natural way for subsequent automated EEG diagnosis. In deriving redundancy reduction encoders, the efficiency of several digital compression techniques has been compared by encoding EEG data. The general approach adopted, however, is not restricted to this class of data, but can be applied (with minor modifications) to other data of similar characteristics.     

Performances comparison of pulse-pair and 2-step prediction algorithms for the doppler spectrum estimation

In this work we use real data provided by terminal pulse Doppler radar (WSR-88D) echoes to estimate the windshear hazards disastrous for the aircraft takeoffs and landings. Briefly two different methods are used to estimate the received Doppler moments. The second central moment which is the variance of the wind speed is called width or shear. A first method is in the time domain and also called pulse-pair, while the second is in the frequency domain. The main aim of this study is a performances comparison of results provided by the two mentioned methods and assumes that the power spectrums of the received signals are approached with the Gaussian shape.     

基于DSP和FPGA的水声定位系统主控机设计

数字信号处理系统是水声学定位系统的核心,本系统采用DSP结合FPGA进行了水声定位系统主控机的设计,给出了硬件框图,介绍了主要组成模块的功能,完成了存储器接口设计、网络接口设计、FPGA逻辑接口设计等设计。调试以及实验结果表明,本硬件系统能够完成合作目标的信号检测与时延估计,满足了水声定位系统的要求。     

Subspace intersection method of high-resolution bearing estimation in shallow ocean using acoustic vector sensors

The subspace intersection method (SIM) provides unbiased bearing estimates of multiple acoustic sources in a range-independent shallow ocean using a one-dimensional search without prior knowledge of source ranges and depths. The original formulation of this method is based on deployment of a horizontal linear array of hydrophones which measure acoustic pressure. In this paper, we extend SIM to an array of acoustic vector sensors which measure pressure as well as all components of particle velocity. Use of vector sensors reduces the minimum number of sensors required by a factor of 4, and also eliminates the constraint that the intersensor spacing should not exceed half wavelength. The additional information provided by the vector sensors leads to performance enhancement in the form of lower estimation error and higher resolution.     

An introduction to the Gaussian least squares approximation and its application in signal processing and system modeling

At the end of the 18th century C.F. Gauss introduced the idea of least squares approximation. This idea is still of fundamental importance today, 200 years later, and has led to the development of many related techniques in signal processing and system modeling. In this paper, a tutorial discussion is given on least squares approximation. Related techniques are presented with examples. These include generalized Fourier analysis, deconvolution and linear prediction, all of which are shown to be closely related to Gauss's original idea.