基于频偏校正的正弦波频率估计算法

提出了一种新的正弦信号频率估计方法。利用FFT对信号频率作粗估计,然后对原信号下变频至基带。对基带信号作相位差分,估计频偏。最后对粗估计进行频率校正,使估计性能得到提高。在整个频段上该方法与R ife算法性能互补,在此基础上又提出了综合方法。仿真结果表明,该频率校正算法实现简单,运算量小,且性能不随被估计信号的频率分布而产生波动,在适度信噪比条件下均方根误差小于1.5倍的CRLB,具有广阔的应用前景。     

基于快速平行因子分解的声矢量传感器阵二维DOA估计

将声矢量传感器阵列参数估计问题与平行因子(Parallel factor,PARAFAC)模型相结合,提出了一种基于快速PARAFAC分解的二维波达方向(Direction of arrival,DOA)估计算法。该算法首先将接收信号构建为PARAFAC模型,然后在数据域对参数矩阵进行初估计,最后利用PARAFAC分解获得信号二维DOA估计。该算法能够应用于任意结构的声矢量传感器阵列,同时能够得到和信源一一匹配的仰角和方位角估计。借助于参数矩阵的初始估计,所提算法收敛速度较快,其计算复杂度大大降低。该算法角度估计性能接近于PARAFAC算法,同时优于借助旋转不变性进行信号参数估计(Estimation of signal parameters via rotational invariance technique,ESPRIT)算法和传播算子(Propagator method,PM)算法。     

基于LMD-PARAFAC的欠定盲源分离

平行因子(Parallel Factor,PARAFAC)作为一种张量数据处理算法,在宽松约束条件下其模型分解具有唯一性。本文将局域均值分解(Local mean decomposition,LMD)和PARAFAC相结合,提出一种新的欠定盲源分离算法。利用局域均值分解得到观测信号的生产函数(Production functions,PF)分量,再与原观测信号组合得到新的观测信号,从而将欠定混合转换为额定或超定混合源分离问题。对新观测信号进行白化预处理并构造为PARAFAC模型,并利用三线性交替最小二乘(Trilinear Alternating Least Square,TALS)算法实现PARAFAC模型分解,从而得到源信号的估计。通过仿真结果表明LMDPARAFAC算法能够从非平稳欠定混合信号中准确估计源信号。将所提算法应用到多机振动源实验中,实验结果进一步验证了该算法的有效性。     

非线性调频信号参数估计算法

分析了非线性调频（NLFM）信号参数估计问题，提出了利用二次相位差分使相位降阶，使NLFM信号的参数估计转化为成熟的正弦波频率估计，而NLFM信号参数估计算法从三维搜索简化为三次一维搜索，既减少了计算复杂度，又有利于工程实现；另外从正弦波频率估计问题出发推导出对信号参数α3估计的最佳相关延迟量为2T/7,向时还考虑了延迟相关对信号信噪比的影响，发现一次延迟相关信号信噪比至少下降3dB，两次延迟相关至少下降7dB，而且信噪比越小，下降越多，因此该算法适用于高信噪比条件，仿真结果表明，该算法在较高的信噪比条件（RSN＞2dB)下具有较好的性能。     

基于HHT的自适应滤波方法在信号处理中的应用

在研究HHT(Hilbert-Huang Transform)理论中经验模态分解方法(EMD)和希尔伯特变换(Hilbert-Huang Transform)方法的基础上,根据IMF信号的时频序列特性,利用聚类算法得到每个时频序列的中心频率和干扰频率,并将与干扰频率对应时刻的IMF时域信号进行分类组合,从而消除IMF信号中的频率混叠问题,实现对信号的自适应滤波。利用所设计方法对实测信号进行自适应滤波分析并与传统数字滤波器滤波数据对比,结果表明提出的方法正确有效。     

双平行线阵中基于Euler变换传播算子的二维DOA估计算法

考虑双平行线阵中非圆信号二维波达方向 (Direction of arrival,DOA) 估计问题,提出了一种基于Euler变换传播算子（Propagator method,PM）的二维DOA 估计算法。该算法利用非圆信号的特性,扩展了接收数据矩阵,使得角度估计性能优于二维PM算法。同时采用Euler变换把非圆PM算法中的复数运算转换为实数运算,降低计算复杂度,角度估计性能逼近非圆PM算法。该算法可以实现二维角度的自动配对,与传统PM算法相比,可同时估计出更多的信源。该算法的优越性均可在文中得到验证。     

广义镜象变换及其在信号特征分析中的应用

本文首先介绍了镜象变换及其性质,并将其推广到复数空间中去,引出了广义镜象变换。广义镜象变换保留着镜象变换的主要特性。然后利用广义镜象变换提出了一种信号特征分析的新算法,即广义镜象变换-QR算法。它包括两大步骤:(1)利用广义镜象变换将Hermite阵化为实对称三对角阵。(2)利用带位移的QR方法求实对称三对角阵的特征值。文中给出了上述算法的详细流程。该算法具有收敛速度快和数值稳定的优点。我们将上述方法用于噪声中信号个数的估计问题,给出了Monte-Carlo模拟结果,验证了所述算法的有效性。在模拟实验中,假定天线阵为均匀线性阵,信号源为两个独立的等功率源,目标模型为Swerling Ⅱ,噪声为空间白色的和高斯的。干扰协方差阵由参考噪声样本估计得到。     

S模式前导脉冲过零点提取与TOA时间戳精确度研究

前导脉冲信号到达时间（Time of arrival，TOA）估计精确度直接影响多点定位精确度。在差分匹配滤波器数学模型基础上，分析理想脉冲信号差分匹配滤波器TOA精确度与采样频率的关系。讨论非理想脉冲信号之间的时间结构关系，提出基于S模式前导四脉冲信号构造差分匹配滤波器校准时间戳的改进算法，实现过零点的准确估计。从信噪比、采样频率和复杂度仿真数据输出的均方根误差对比可见，通过四脉冲滤波获得的TOA精确度要比单脉冲和双脉冲滤波获得TOA精确度高。匹配滤波器和差分匹配滤波器TOA精确度对比分析结果表明，修正的差分匹配滤波器算法有更好的效果。在采样频率 40 MHz、信噪比为40 dB时，四脉冲信号差分匹配滤波器TOA精确度为0.402 7 μs，远远小于国际民航组织规定的时间误差精度最大值25 μs。最后实际空管运行数据验证结果证明了本文修正算法估算TOA的精确度和可用性。     

基3FFT与FHT的新算法

本文首先提出了适合于N=3~m的按频率抽取快速Fourier变换(DIF FFT)与按时间抽取快速Fourier变换(DIT FFT)的新算法,分别导出了算法的一般公式,给出了信号流图,分析了计算复杂性。对于实序列的FFT算法也相应作了探讨,然后按照类似的方式提出了适合于N=3~m的按频率抽取快速Hartley变换(DIF FHT)与按时间抽取快速Hartley变换(DIT FHT)的新算法。最后将本文提出的基3FFT算法、基3FHT算法与其他基3算法进行了比较。结果表明,新算法不仅所需运算量少,优于其他基3算法,而且可进行原位计算,结构简单规则,易用硬件或软件实现。本文算法扩展了FFT算法与FHT算法的可适用范围。     

Computationally Efficient MUSIC-Based Algorithm for Joint Direction of Arrival (DOA) and Doppler Frequency Estimation in Monostatic MIMO Radar

The problem of joint direction of arrival (DOA) and Doppler frequency estimation in monostatic multiple-input multiple-output (MIMO) radar is studied and a computationally efficient multiple signal classification (CE-MUSIC) algorithm is proposed.Conventional MUSIC algorithm for joint DOA and Doppler frequency estimation requires a large computational cost due to the two dimensional (2D) spectral peak searching.Aiming at this shortcoming,the proposed CE-MUSIC algorithm firstly uses a reduced-dimension transformation to reduce the subspace dimension and then obtains the estimates of DOA and Doppler frequency with only one-dimensional (1D) search.The proposed CE-MUSIC algorithm has much lower computational complexity and very close estimation performance when compared to conventional 2D-MUSIC algorithm.Furthermore,it outperforms estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm.Meanwhile,the mean squared error (MSE) and Cramer-Rao bound (CRB) of joint DOA and Doppler frequency estimation are derived.Detailed simulation results illustrate the validity and improvement of the proposed algorithm.     

A Real-Valued 2D DOA Estimation Algorithm of Noncircular Signal via Euler Transformation and Rotational Invariance Property

The problem of two-dimensional(2 D)direction of arrival(DOA)estimation for double parallel uniform linear arrays is investigated in this paper.A real-valued DOA estimation algorithm of noncircular(NC)signal is proposed,which combines the Euler transformation and rotational invariance(RI)property between subarrays.In this work,the effective array aperture is doubled by exploiting the noncircularity of signals.The complex arithmetic is converted to real arithmetic via Euler transformation.The main contribution of this work is not only extending the NC-Euler-ESPRIT algorithm from uniform linear array to double parallel uniform linear arrays,but also constructing a new 2 Drotational invariance property between subarrays,which is more complex than that in NCEuler-ESPRIT algorithm.The proposed 2 DNC-Euler-RI algorithm has much lower computational complexity than2 DNC-ESPRIT algorithm.The proposed algorithm has better angle estimation performance than 2 DESPRIT algorithm and 2 D NC-PM algorithm for double parallel uniform linear arrays,and is very close to that of 2 D NC-ESPRIT algorithm.The elevation angles and azimuth angles can be obtained with automatically pairing.The proposed algorithm can estimate up to 2(M-1)sources,which is two times that of 2 D ESPRIT algorithm.Cramer-Rao bound(CRB)of noncircular signal is derived for the proposed algorithm.Computational complexity comparison is also analyzed.Finally,simulation results are presented to illustrate the effectiveness and usefulness of the proposed algorithm.     

Low-Complexity DOA Estimation of Noncircular Signals for Coprime Sensor Arrays

This paper presents a low-complexity method for the direction-of-arrival(DOA)estimation of noncircular signals for coprime sensor arrays. The noncircular property is exploited to improve the performance of DOA estimation. To reduce the computational complexity,the rotational invariance propagator method(RIPM)is included in the algorithm. First,the extended array output is reconstructed by combining the array output and its conjugated counterpart. Then,the RIPM is utilized to obtain two sets of DOA estimates for two subarrays. Finally,the true DOAs are estimated by combining the consistent results of the two subarrays. This illustrates the potential gain that both noncircularity and coprime arrays provide when considered together. The proposed algorithm has a lower computational complexity and a better DOA estimation performance than the standard estimation of signal parameters by the rotational invariance technique and Capon algorithm. Numerical simulation results illustrate the effectiveness and superiority of the proposed algorithm.     

Weak GPS L1 Signal Acquisition Based on BPDC

It is difficult to achieve accurate acquisition of weak global positioning system（GPS） signals with traditional methods. A weak signal acquisition strategy based on block processing and differentially coherent （BPDC） is put forward after analyzing the advantages and disadvantages of coherent and non-coherent integration algorithms. Code phase parallel search of the pre-coherent integration is conducted by using fast Fourier transform（FFT）, and the results are then differential coherent processed and block processed. BPDC method reduces computation cost compared with coherent and non-coherent（CNC） algorithm. The performance of the two algorithms is also compared based on simulated signals. The result shows that the noise suppression effect of BPDC algorithms is superior to that of traditional CNC algorithm, and the superiority of BPDC is more apparent with the reduction of carrier to noise ratio （CNR）. In the case that the pre-coherent integration length is 4 ms and CNR is reduced to 28 dB-Hz, CNC algorithm cannot yet acquire signal correctly while BPDC has well acquisition performance. Therefore, for weak GPS signal acquisition, BPDC algorithm can acquire the signal with lower CNR and has better acquisition property.     

基于倒序相关累加的信号到达时间盲估计

研究了在信号频率、初相、幅度未知条件下,矩形包络复正弦信号到达时间盲估计算法.先利用相关检测对信号的起、止时间进行粗估计,估计出信号频率,并将其变换到基带,经倒序累加后的信号模值,在到达时刻将出现拐点并达到最大输出信噪比,检测出拐点位置,作为到达时间精估计.文中推导了离散矩形包络复正弦信号到达时间估计的克拉美罗限.计算机仿真表明,本方法在较低信噪比条件下可实现对信号到达时间的精确估计.     

谐波小波在信号滤波中的应用

谐波小波在频域具有良好的盒形谱特性 ,另外它比通常由二进尺度函数得到的小波还具如下优越性 :存在确定的函数表达式 ;时频定位更加准确 ;算法实现简单 ;可以得到任意频率段的信号。本文重点对谐波小波在数字信号滤波中的应用进行研究     

宽带信号的数字测向算法研究

数字测向是电子侦察领域的一项重要内容。本文介绍了多基线测向算法,时其解模糊原理及范围作了深入分析,并给出了常见宽带信号的数字鉴相算法。该算法时这些宽带信号采用非线性变换,将其变为常规信号后进行处理,估计出该宽带信号的方向。本算法在较低信噪比条件下仍有较高精度。