改进SSMUSIC超分辨多径时延估计算法

传统的MUSIC超分辨时延估计技术是直接基于测量数据,其性能往往只对宽带且频谱近似平坦的信号较优,而对窄带信号估计性能较差。针对上述问题,本文通过利用谐波频率估计模型和DOA (Direction of Arrival)估计模型之间的等价性,将时延估计问题转化为谐波频率估计问题,提出了一种改进SSMUSIC(Signal Subspace Scaled Multiple Signal Classification)超分辨多径时延估计算法。改进后的算法采用平滑的思想和SSMUSIC算法的思想构造协方差矩阵和MUSIC谱,实现了对多径时延的超分辨估计。仿真表明,该算法能够实现对窄带信号多径时延超分辨估计且具有DP(Direct-Path)不模糊和谱峰陡峭的特点,估计性能优于传统的超分辨算法。      

宽带接收机的窄带信号频率 和二维角度估计新方法

 针对宽带接收机对窄带信号进行频率和二维到达角(DOA)估计问题,本文提出了一种新的快速频率和角度估计方法,该方法首先利用参考频率进行DOA预估计,然后利用空域滤波有效地将频率和预估计DOA进行匹配,并根据天线阵列的结构特点利用信号的相应频率进行预估计DOA校准,获得了信号的准确频率和DOA估计值.最后的仿真分析验证了所提出方法的正确性和有效性.     

宽带独立信号和相干信号的DOA估计

当独立信号和相干信号共存时,传统四阶累积量方法无法估计出宽带相干信号的来波方向(DOA),针对这个问题提出了一种新方法。该方法首先通过离散傅里叶变换,将宽带阵列接收数据分解为若干个窄带信号,构造出各个窄带频率处的自相关矩阵,再通过MUSIC(Multiple Signal Classification)算法估计出各个窄带信号的DOA,将各个窄带信号的空间谱相加求平均,通过谱峰搜索得到宽带独立信号的DOA;然后分离出独立信号的信息,构造出一个只包含宽带相干信号信息的矩阵,最后通过稀疏重构的方法估计出相干信号的DOA。计算机仿真结果证明该算法的正确性和有效性。     

低信噪比情况下调频信号的瞬时频率估计

提出一种基于互Wigner-Ville分布(XWVD)的瞬时频率迭代估计方法.理论分析了该方法的收敛性,通过仿真比较了各种瞬时频率估计方法在噪声下的估计方差,证明此方法在低信噪比情况下对估计线性调频信号的瞬时频率有较好的效果.并采用加窗的方法改进了此算法,仿真结果证明,改进的方法对非线性调频信号的瞬时频率进行了有效估计.     

基于GTD模型的多视角多波段窄带雷达信号融合

研究了窄带雷达信号融合问题,提出了一种基于GTD(Geometrical Theory of Diffraction)模型的窄带雷达信号多视角多波段融合的方法.在同波段多视角融合方面,利用Lincoln实验室的方法给出模型参数的初值,再运用遗传算法对参数进行迭代寻优.而在不同波段多视角融合方面,则利用视角融合后获得的同角度不同波段窄带信号联合估计频率衰减因子.并通过仿真实验以二维条带目标为例验证了方法的有效性.     

一种基于稀疏分解的窄带信号频率估计算法

针对窄带多分量信号频率估计问题,该文提出一种基于稀疏分解的频率估计算法,能够同时对多个窄带信号的频率进行估计。首先利用传统方法进行频率预估计,然后根据频率预估计的结果建立冗余字典,对信号进行稀疏表示,最后通过匹配追踪算法得到精确的频率估计。该算法极大地减小了字典的长度和稀疏分解的运算量,而且在迭代过程中利用了全局信息更新残差向量,估计结果更为精确,在低信噪比情况下性能也较为稳健。仿真结果验证该算法的有效性和正确性。     

宽带信号源的波达方向估计新方法

针对信号源数多于天线阵元数的情况,提出了一种新的宽带信号波达方向(DOA)的估计方法.与传统方法一样,首先把宽带信号分解为互不重叠的窄带部分,通过将信号频率的不同等效为阵元间距的不同而得到多个阵列,合理组合这些阵列可以获得一个多阵元的虚拟阵列,对此虚拟阵列的输出运用传统的窄带信号子空间方法即可进行高分辨DOA估计.不需要对阵列输出进行"聚焦"变换及角度预估计,并且利用两个阵元即可对多个宽带信号进行空间谱估计.仿真结果证明了该方法在信号源数多于阵元数情况下的有效性.     

空间相干源信号频率和波达方向的同时估计方法

本文针对宽频段窄带相干信号源,充分利用多重信号分类和旋转不变两大技术,结合一定的时域信息,提出了一种高精度的信号频率和波达方向同时估计方法.该方法通过构造平滑波达方向矩阵进行参数估计,无需搜索过程和配对处理.计算机仿真验证了本文所提出方法的有效性.     

宽波束高频雷达的超分辨率时-空级联处理

针对在宽波束高频雷达目标探测中传统傅立叶变换频谱分析方法多普勒分辨率较低的问题,提出了一种全超分辨率的时-空域级联信号处理方法.首先利用多重信号分类(MUSIC)算法获得频域超分辨率谱估计,构造出相应于各信号频率的信号子空间,将原始信号向各子空间进行投影变换以获得相应于各信号频率的阵列快拍,然后利用其进行空域超分辨率谱估计,获得相应的到达角.利用该方法能有效地采用短相干积累时间进行多目标的频率-到达角参数估计,从而有效地提高了宽波束高频雷达的目标探测和跟踪性能.数值仿真实验验证了该方法的有效性.     

广义谱相关子空间拟合DOA估计原理

本文提出了一种用广义谱相关信号子空间拟合进行波达方向估计的方法,该方法同时适用于宽带与窄带信号的DOA估计,在窄带情形下还能够大大提高阵列的等效孔径.理论分析表明,目前几种主要的循环平稳DOA估计方法(如SC-SSF,Cyclic MUSIC,Cyclic ESPRIT)均可看作是该方法的特例或近似.最后,仿真结果证明了该方法的有效性与一般性.     

广义Pareto分布海杂波模型参数的组合双分位点估计方法

广义Pareto分布的复合高斯模型可以很好地描述高分辨低擦地角对海探测场景中海杂波的重拖尾特性,实现该杂波模型下双参数的有效估计对雷达检测性能具有重要意义。对此,该文提出一种双参数的组合双分位点(CBiP)估计方法。该估计方法基于低阶多项式方程的显式求根表达式,充分组合利用回波中的样本信息,旨在实现高精度的双参数估计过程。此外,考虑到实际雷达工作中存在岛礁、渔船等造成的功率异常大的野点样本时,不同于传统的矩估计、最大似然(ML)估计等方法,组合双分位点估计方法仍可保持估计性能的鲁棒性。仿真及实测数据实验表明,在纯杂波环境中,组合双分位点估计方法可以实现与最大似然估计方法近似的估计精度,若存在异常样本,组合双分位点估计方法的估计性能优于上述几种传统估计方法。     

Distributed multichannel speech enhancement with minimum mean-square error short-time spectral amplitude, log-spectral amplitude, and spectral phase estimation

In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time spectral amplitude (STSA), log-spectral amplitude (LSA), and spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products.     

Analysis and design of joint CFO/channel estimate techniques for a cooperative STBC‐OFDM system

This paper studies the joint estimation technique of carrier frequency offset (CFO) and channel information for a distributed decode‐and‐forward (DF) cooperative space‐time block‐coded (STBC) orthogonal frequency division multiplexing (OFDM) system. For the considered relay system, we provide theoretical analysis of the effects upon the output signal‐to‐noise ratio (SNR), which is caused by the CFO/channel estimation error. Based on the provided analytical results, a joint CFO/channel estimation scheme is then developed, where the CFO estimate is achieved by a multiple‐dimensional linear search algorithm. Furthermore, we propose an alternative estimation solution with iteration approach being designed for the CFO estimation prior to the channel estimation. In contrast to the former estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. The conducted computer simulation results verify the effectiveness of the proposed schemes.     

A NOVEL INTEGER FREQUENCY OFFSET ESTIMATOR FOR OFDM

One of the principal disadvantages of Orthogonal Frequency Division Multiplexing （OFDM） is very sensitive to carrier frequency offset. The integer frequency offset has no effect on the orthogonality among the subcarriers, but it causes a circular shift and phase rotation of the received data symbols sequence, resulting in a Bit Error Rate（BER） of 0.5. In this paper, a novel integer frequency offset estimator for OFDM is derived based on maximum likelihood estimation technique and exploration of the differential relation between two consecutive OFDM data symbol sequences in frequency domain. Its performance is compared with the conventional method by computer simulations for the additive white Gaussian noise channel and a multipath fading channel. Simulation results show that the performance of the proposed estimator is better than the conventional estimator.     

Frequency Offset Estimation by Multi-Band Averaging Method: A New Approach for MB-OFDM Based Ultra-Wideband Communication System

In this literature, we present a new method for estimating the coarse frequency offset in multi-band orthogonal frequency division multiplexing (MB-OFDM) based ultra-wideband (UWB) communication systems. The proposed training based coarse frequency offset (CFO) estimator performs an averaging of initial estimate over the multiple bands of transmission during estimation process. The proposed multi-band averaging provides an improved estimation of approximately three times for band group 1 (BG1) compared to our earlier proposed scheme. To prove the efficiency of the proposed scheme, the Cramer Rao lower bound (CRLB) of the estimation error is calculated and compared with the simulation results. We illustrate the performance of MB-OFDM system in terms of bit-error rate (BER) with multi-band averaged frequency synchronization (MBAFS) and compare with earlier reported results for 100,000 noisy realizations in UWB channel model 2 (CM2).     

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO–OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO–OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator.     

Joint Angular- and Delay-Domain MIMO Propagation Parameter Estimation Using Approximate ML Method

In this paper, we derive an estimation method that jointly estimates the parameters of the concentrated propagation paths and the distributed scattering component that are frequently observed in multiple-input multiple-output (MIMO) channel sounding measurements. The joint angular-delay domain model leads to a correlation matrix with high dimensionality, which makes direct implementation of a maximum-likelihood (ML) estimator unfeasible. We derive low-complexity methods for computing approximate ML estimates that exploit the structure of the covariance matrices. We propose an iterative two-step procedure that alternates between the estimation of the parameters of the concentrated propagation paths and the parameters of the distributed scattering. For the distributed scattering, the estimator first optimizes the parameters describing their time-delay structure. Then, using the estimated time-delay parameters, the parameters of the angular distributions are optimized. We present simulation results and compare the estimated time-delay and angular distributions to the actual distributions, demonstrating that high-quality estimates are obtained. The large sample performance of the estimator is studied by establishing the Cramer-Rao lower bound (CRLB) and comparing it to the variances of the estimates. The simulations show that the variance of the proposed estimation technique reaches the CRLB for relatively small sample size for most parameters, and no bias is observed.     

Structured total least squares approach for efficient frequency estimation

A new structured total least squares (STLS) based frequency estimation algorithm for real sinusoids corrupted by white noise is devised. Numerical results are included to contrast the estimator performance with an existing STLS frequency estimation method as well as the Cramér-Rao lower bound in different signal-to-noise ratio conditions.     

OFDM Carrier Frequency Offset Estimation Methods With Improved Performance

Orthogonal frequency division multiplexing (OFDM) systems are highly sensitive to carrier frequency offset and symbol timing error. This paper deals with estimation method of integer frequency offset (IFO) without the aid of pilot symbols. The proposed IFO estimator exploits two consecutive identical OFDM data symbols with only change of phase. In order to improve the accuracy of the IFO estimator, receive diversity is adopted. To demonstrate the efficiency of the proposed IFO estimators, comparisons are made with other existing estimators in terms of error performance, estimation range, and complexity.     

Frequency and Timing Offset Estimation Using Single Reference Symbol

In this paper we will investigate the performance of an estimator employing single OFDM reference symbol for timing and frequency offset estimation. We will show how both coarse and fine frequency offset estimation can be performed with this single OFDM reference symbol. The performance of this estimator will be compared with the ML estimator employing OFDM reference symbols of different length for coarse and fine frequency offset estimation. It will be shown that, unlike ML estimator, the estimation range of the analyzed estimator is not constrained.