基于单电磁矢量传感器的多参数联合估计

利用电磁矢量传感器来实现信号多参数的联合估计是近年来信号处理领域的一种新的方法和途径。基于单个电磁矢量传感器通过构造两组具有固定时延的接收数据,利用TLSESPRIT算法和矢量叉积相结合实现了多参数的联合估计,参数自动完成配对,可以最多同时估计5个不相关的信号,且空间到达角、极化参数的估计和信号频率的估计是两个相互独立的过程互不影响,与利用极化敏感阵列进行参数估计相比计算量小,并通过计算机仿真验证了此方法的有效性。     

基于矢量传感器MIMO雷达的发射极化优化DOA估计算法

针对常规矢量传感器MIMO雷达没有利用发射极化信息导致波达方向(DOA)估计精度较差的问题,该文提出一种克拉美罗界(CRB)最小化的发射极化优化算法。首先建立矢量传感器MIMO雷达的接收信号模型;然后分析固定发射极化矢量传感器MIMO雷达DOA估计算法的不足;接着推导任意发射极化状态下的CRB,计算最小CRB对应的极化状态;最后利用该优化极化状态采用固定极化DOA估计算法得到DOA估计。该算法的DOA估计精度高于固定极化DOA估计算法。且该算法的2维DOA估计可自动配对,发射电磁矢量传感天线位置可任意。仿真结果证明了该算法的有效性。     

部分极化波参数估计方法的改进

该文提出了基于矢量传感器的部分极化波信号参数估计方法的一种改进方法。该方法充分利用一次特征分解的特征值和特征矢量估计部分极化波的到达角和极化度,信号参数自动配对,降低了运算量,提高了参数估计的精度,且能够得到信号的空间导向矢量,可以利用阵列孔径信息进一步提高参数估计的精度。数值模拟结果证明该方法是有效的。     

极化信号频率、二维到达角和极化参数的同时估计

本文研究基于标量传感器和/或空域完全伸展矢量传感器极化敏感时间双采样、空间欠采样阵列的多个宽频段窄带极化信号中心频率、二维波达方向和极化参数的同时估计问题。针对时、空多分辨采样数据,利用旋转不变参数估计方法分别估计出与信号频率有关的时间相位因子和对应的含有空间相位信息的所谓混合导向矢量。对估计出的信号时间相位因子的模和相角进行联合,获得模拟频率估计:利用混合导向矢量中还包含的与空间采样间隔无关的极化-角度相干结构信息去除方向余弦估计中的整周模糊并获得相应的极化参数估计。     

矢量传感器阵列MIMO雷达高精度二维DOA与极化联合估计

该文采用矢量传感器配置下的十字型阵列MIMO雷达系统,提出一种新的2维高精度DOA与极化参数联合估计算法。首先根据MIMO雷达虚拟阵列导向矢量的特点,通过降维矩阵的设计及回波数据的降维变换,将高维回波数据转换至低维信号空间;然后基于传播算子获得对应信号子空间的估计,利用收、发阵列阵元间长基线对应的旋转不变性和极化矢量中电场矢量和磁场矢量的叉积进行2维高精度DOA估计和解模糊处理,同时利用与阵列结构无关的极化域旋转不变性进行极化辅角和极化相位差的联合估计。该矢量传感器MIMO雷达阵列可同时获取MIMO雷达的波形分集和矢量传感器的极化分集,无需额外增加阵元和硬件开销,能够有效扩展阵列孔径,提高参数估计性能;同时通过降维变换及传播算子,在获取信噪比增益的同时,能够实现2维高精度DOA和2维极化矢量的联合估计及参数的自动配对,有效降低数据处理维数和参数估计的运算复杂度;最后,仿真结果验证了理论分析的正确性和算法的有效性。     

单有向电磁矢量传感器的参数估计方法

传统的单电磁矢量传感器(UEMVS)由3个电偶极子和3个磁环构成且方向图是全向的。但是当多个单电磁矢量传感器依附在共形载体上构成共形电磁矢量传感器阵列时,为了降低共形电磁矢量传感器阵列的副瓣,通常每个传感器的方向图是有向的。基于有向方向图的单电磁矢量传感器也称为单有向电磁矢量传感器(UDEMVS)。该文针对UDEMVS的参数估计问题,提出两种参数估计方法,分别是基于免搜索的旋转不变信号参数估计和矢量叉积(ESPRIT-VCP)方法以及基于网格搜索的多重信号分类和最小瑞利商(MUSIC-MRQ)方法。ESPRIT-VCP方法是根据旋转不变性和矢量叉积,获得4维参数的闭式解,MUSIC-MRQ方法根据信号和噪声子空间正交性与最小瑞利商,利用网格搜索得到2维角度估计值,进而结合信号回波模型得到2维极化的估计值。所提两种方法只利用了UDEMVS的6通道数据就能有效得到目标的参数估计结果,有较低的计算复杂度。仿真结果从角度和极化的估计性能出发验证了所提方法的有效性。     

信号DOA和极化信息联合估计的降维四元数MUSIC方法

基于简化电磁矢量传感器阵列,该文提出了一种新的降维四元数MUSIC估计方法。文中引用了四元数的概念,利用四元数的正交特性能够很好地描述矢量传感器阵元的正交结构这一优点,建立了电磁矢量传感器阵列的四元数模型,利用降维Q-MUSIC (Quaternion-MUSIC)方法先对极化信号DOA进行估计,通过已经估计出来的DOA信息,再借助传统的V-MUSIC (long-MUSIC)方法估计极化信息。从而依次获得极化信号的4个参数。仿真实验验证了算法的可行性。     

原位误差情况下DOA和极化参数盲估计

现有基于电磁矢量传感器的波达方向(DOA)和极化参数联合估计算法中,均假设电磁矢量传感器的三个电偶极子和三个磁偶极子严格指向参考坐标系,即不存在原位误差.当电磁矢量传感器存在未知原位误差时,其实际极化-角度域导向矢量与理想情况下的极化-角度域导向矢量产生一定的偏差,导致现有算法的估计性能显著下降.基于极化-角度域导向矢量的一阶Taylor近似展开,给出一种原位误差情况下DOA和极化参数的盲估计算法和各参数估计的CRB界.仿真结果表明,在存在原位误差的情况下,该方法的估计性能明显优于传统方法.     

一种矢量传感器阵列误差的自校正算法及DOA估计

突破大多数阵列误差校正技术针对标量传感器阵列误差模型的限制,提出一种对电磁场矢量传感器阵列误差进行自校正的方法。该方法针对存在方位依赖阵元幅相误差的矢量传感器阵列模型;所提算法基于子空间的思想可对任意极化状态多源信号的信源方位、极化参数和对应的阵元幅相误差进行无模糊联合估计;该方法适用于具有任意几何结构的矢量传感器阵列,仿真试验表明了该算法的有效性。     

电磁矢量传感器原位误差校正方法

 现有基于电磁矢量传感器阵列的信号DOA和极化参数联合估计算法,大都假设电磁矢量传感器的三个电偶极子和三个磁偶极子严格指向参考坐标系的三个坐标轴,即不存在原位误差.然而在实际应用场合,电磁矢量传感器是存在原位误差的,因此其实际极化-角度域导向矢量与理想情况下的极化-角度域导向矢量有一定的偏差,导致现有方法的估计性能显著下降,因此必须对原位误差进行校正.通过对存在偏差的极化-角度域导向矢量进行一阶Taylor近似展开,并利用一个辅助校正源,提出了电磁矢量传感器原位误差校正方法,给出了原位误差估计的CRB界.仿真结果验证了该方法的有效性.     

矢量传感器误差校正与补偿

当阵列模型存在误差时,子空间类方法的高分辨性能会显著下降,因此必须进行有效的校正。由于矢量天线本身的复杂性,其相位误差很难精确校准且原有的基于标量天线相位误差的估计方法已经不再适应于矢量天线。该文在到达角已知情况下,给出了一种估计矢量天线阵列相位误差的新方法,并导出了各通道相位误差的计算公式。最后的数值模拟结果说明了本文方法是简单有效的。     

用于MIMO-OFDM无线通信系统的一种新的自适应半盲波束形成算法

该文根据MIMO-OFDM物理层结构和无线移动矩阵信道的特性,从神经网络和信息论观点详细推导了一种新的多天线阵列自适应半盲波束形成器算法。与常规的盲估计和导频辅助信道估计算法不同的是,本文提出的新的半盲算法在权矢量自适应更新时,不断地用基于导频估计的权矢量进行修正。最后,用实际的HIPERLAN2协议进行了计算机仿真。结果表明这种算法不增加发射信号功率和不占用额外带宽,能提高天线增益性能和有效地提取出期望的发射信号,在收敛速度和BER性能方面优于常规的导频辅助信道估计算法。该波束形成器能自适应调整权矢量,其更新方式与TDMA和CDMA相似,所以本算法可直接用于有天线阵列的基于OFDM的第三代(3G)和三代后(3G beyond)的无线通信系统。     

未知接收机通道特性下的信号“空间特征”估计算法

该文用均匀线阵研究了未知接收机通道特性下信号“空间特征”“w=2π△sinθ/λ)的估计问题,利用均匀线阵的冗余结构,本文给出了基于信号子空间的ESPRIT－Like算法,得到了一个信号“空间特征”和通道特性的近似解,ESPRIT－Like算法对信号“空间特征”估计具有较好的稳健性;与B.Friedlander,V.C.Soon等人（1994）提出的其它迭代算法相比,ESPRIT－Like算法具有计算量小的优点,数值仿真结果证实了本文算法的有效性并评价了算法的性能。     

A novel blind estimation algorithm

In this paper, we propose a cumulant-based blind signal estimation algorithm for estimating the channel matrix in an n-sensor m-source system. The only available information is the output of the n sensors. The algorithm first deduces the number of sources, which may be greater than or equal to the number of sensors, from the output cumulant matrix. Then, by suitably arranging the elements within that matrix, the entries of the original channel matrix are estimated row by row. Simulations results are given to illustrate the performance of the algorithm     

Double differential space-time block coding for time-selectivefading channels

Most existing space-time coding schemes assume time-invariant fading channels and offer antenna diversity gains relying on accurate channel estimates at the receiver. Other single differential space-time block coding schemes forego channel estimation but are less effective in rapidly fading environments. Based on a diagonal unitary matrix group, a novel double differential space-time block coding approach is derived in this paper for time-selective fading channels. Without estimating the channels at the receiver, information symbols are recovered with antenna diversity gains regardless of frequency offsets. The resulting transceiver has very low complexity and is applicable to an arbitrary number of transmit and receive antennas. Approximately optimal space-time codes are also designed to minimize bit error rate. System performance is evaluated both analytically and with simulations     

Decision fusion in mobile wireless sensor networks using cooperative multiple symbol differential space time coding

In this article, we propose a cooperative scheme for differential space-time codes (DSTCs) to be applied for mobile wireless sensor networks (WSNs) in order to mitigate multipath fading effect. We assume that sensors make independent local decisions about the existing hypothesis and report their decisions to a fusion center, where the final decision is made. Sensors are divided into groups with two sensors each, where sensors in each pair cooperate to send their decisions as a DSTC. Differential modulation scheme, which does not require knowledge of the instantaneous fading gains, is considered to avoid the channel estimation overhead at the cooperating sensors and the fusion center. Channels between sensors and the fusion center are assumed independent identically distributed (i.i.d) Rayleigh fading channels. Moreover, Jakes-Clarkes’ channel model is considered to model the mobility of sensors and/or the fusion center. Since the complexity of the optimal fusion rule grows up exponentially with the observation interval, suboptimal fusion rules are derived and discussed. Finally, simulation results of the proposed cooperative scheme are provided and the detection capabilities of the derived decision fusion rules are compared.     

Vector-sensor array processing for electromagnetic sourcelocalization

The authors present a new approach for localizing electromagnetic sources using sensors where the output of each is a vector consisting of the complete six electric and magnetic field components. Two types of source transmissions are considered: (1) single signal transmission (SST), and (2) dual signal transmission (DST). The model is given in terms of several parameters, including the wave direction of arrival (DOA) and state of polarization. A compact expression is derived for the Cramer-Rao bound (CRB) on the estimation errors of these parameters for the multi-source multi-vector-sensor model. Quality measures including mean-square angular error (MSAE) and covariance of vector angular error (CVAE) are introduced, and their lower bounds are derived. The advantage of using vector sensors is highlighted by explicit evaluation of the MSAE and CVAE bounds for source localization with a single vector sensor. A simple algorithm for estimating the source DOA with this sensor is presented along with its statistical performance analysis     

The estimation of the directions of arrival of the spread-spectrum signals with three orthogonal sensors

An effective technique in estimating the directions of arrival (DOAs) of incoming signals using three orthogonal sensors is proposed. The channel model with multipath transmissions for code-division multiple access (CDMA) users whose signals are modulated with binary phase-shift keying (BPSK) is used. Utilizing the maximum-likelihood (ML) method, the channel impulse response vectors of the three sensors can be estimated, then all of the corresponding propagation delays and amplitude weights of the three sensors' channels can be obtained. By comparing the propagation delays of the three channels, we can identify the same signal replica, then its DOA can be estimated by the relation of the three corresponding attenuation weights. Calculating results show this method can reach fairly high accuracy, and it needs only three sensors while in other techniques the required number of sensors is greater than the number of estimated signals.     

Analysis of the Principal Component Combining with Weight Estimation for DPSK Signals

We analyze the principal component combining with differential detection (PCC-DD) with weight estimation for the demodulation of DPSK signals in diversity systems. The estimated weight vector is considered to be the principal component of the exponentially weighted sample correlation matrix of the signals at diversity channel outputs. We arrive at closed form expressions for the approximate bit error rate (BER) for the scenario where channel gains are fixed, and the approximate average BER for the scenario where channel gains are independent identically Rayleigh distributed. The analysis provides accurate BER approximation, and is justified by the results from computer simulations. We also arrive at a rule of thumb about the value of the forgetting factor of the exponentially weighted sample correlation matrix should be selected for PCC-DD to yield good performance under time varying Rayleigh fading channels     

频带FSO-OFDM系统建模与LS信道估计研究

本文首先设计了频带FSO-OFDM系统模型,阐述了其发射和接收部分工作原理,介绍了大气散射信道模型。通过对散射信道的仿真,发现FSO-OFDM系统对弱散射有很强的抵御能力,当散射强度强时,系统性能就会急剧恶化,由于提高发射功率不能有效的降低散射对系统的影响,为了解决此问题,本文利用璩算法对导频处大气信道进行估计,最后通过插值恢复出数据处信道参数,通过仿真进行验证,结果表明,通过合理设计导频序列,IS算法能够很好的改善强散射信道中频带FSO-OFDM系统性能。