MIMO雷达DOD和DOA联合估计算法: RTR-ESPRIT

 针对双基地多输入多输出(MIMO)雷达多目标波离角(DOD)和波达角(DOA)的联合估计问题,提出一种接收-发射-接收(RTR)-ESPRIT算法。该算法首先利用一维接收ESPRIT(R-ESPRIT)预估计目标DOA,随后分别利用一维发射ESPRIT(T-ESPRIT)和一维接收ESPRIT得到目标的高精度DOD和DOA估计,在每两次ESPRIT算法之间分别构造正交投影算子对接收信号进行接收波束形成和发射波束形成。与传统ESPRIT算法相比,该算法大大降低了数据协方差矩阵维数和计算复杂度,无需额外的配对算法,且理论证明了该方法还可以用于相干目标和单快拍情况下DOD和DOA的联合估计。仿真结果表明了该算法的正确性及良好的估计性能。     

机载共形阵天线阵列信号处理的关键技术分析

机载共形阵是机载有源相控阵天线发展的下一个目标。共形阵天线的阵元具有不同的方向性,空间分辨率算法必须考虑来波的极化问题。本文研究了空间信号波达方向(Direction of Arrival,DOA)估计算法的现状,分析了一种适用于共形阵天线空域自适应波束形成的高速滤波算法。     

基于稀疏表示和近似(e)0范数约束的宽带信号DOA估计

针对宽带信号的波达方向(DOA)估计问题,在稀疏框架下提出一种近似(e)0范数约束的宽带信号DOA估计新算法.首先对宽带信号进行预处理,得到同一参考频率点下的接收数据,然后对其协方差矩阵元素进行加和平均运算,得到一个低维的观测向量,并在稀疏框架下进行稀疏表示,最后利用截断(e)1函数设定权值,构造逼近(e)0范数约束的稀疏重构方法,进而重构信号,获得宽带信号的DOA估计.仿真结果表明,相比于传统的宽带信号DOA估计算法,所提算法具有更高的分辨率和估计精度.     

未知互耦条件下混合信号波达方向估计

阵列天线互耦对导向矢量的扰动以及信号相干性对数据协方差矩阵造成的秩损,使得基于子空间正交性原理的超分辨波达方向估计(Direction-of-Arrival,DOA)算法性能恶化,甚至失效。针对这一问题,提出一种在相干与非相干信号混合状态下无需阵列互耦补偿的特征矢量平滑DOA估计算法。该算法对部分阵元接收数据的协方差矩阵特征分解,将得到的特征矢量平滑处理后构造等效协方差矩阵,抑制阵列互耦影响的同时完成混合信号DOA估计。在阵列互耦和信号相干性均未知的条件下,正确估计了信号DOA,无需互耦参数估计或补偿。计算机仿真结果验证了算法的有效性。     

鲁棒成形极化敏感阵列波束的方法及极化估计

基于极化敏感阵列,提出了一种鲁棒成形阵列波束的方法。该方法首先将阵列的数据模型进行了重新描述,从而获得了信号波达角(DOA)和极化解耦的模型。借助于该模型并对信号的两个极化方向分别进行鲁棒约束,设计出了一个新的鲁棒空域波束空间成形矩阵,利用该矩阵可以获得信号两个极化分量的鲁棒估计。基于特征值分解的方法,最后给出了估计信号极化参数的方法。分析和数值仿真实验均表明:提出的方法,在对DOA估计误差以及阵列位置误差等造成的阵列失配具有较强鲁棒性的同时,也能有效抑制干扰和噪声,进而提升了极化参数估计的性能。     

基于空域稀疏性的宽带DOA估计

利用宽带阵列接收信号的空域稀疏性,将宽带信号的波达方向(DOA)估计转化为一个稀疏信号重构的问题,提出了一种新的宽带信号DOA估计算法。该算法将宽带信号分解为多个子带信号,联合利用多个子带信号的空域稀疏性进行重构。它是对用于稀疏重构的标准的稀疏贝叶斯学习算法的推广,可适用于多冗余字典的信号模型。另外,通过对多快拍的阵列接收信号进行奇异值分解(SVD),提取信号子空间作为算法的输入数据,可以在有效减少运算复杂度的同时,提高对噪声的稳健性。与传统的宽带阵列DOA估计方法相比,该算法能够用于低信噪比、快拍有限和信源相关性较高的场合,同时算法的性能对信源个数的估计值不太敏感。仿真实验表明,该算法相对现有的基于子空间类的方法,具有更好的DOA估计性能。     

基于压缩感知的频率和DOA联合估计算法

波达方向（DOA）估计是阵列信号处理的一个重要问题,针对信号的DOA估计问题,本文基于压缩感知理论,提出了一种新的频率和角度联合估计算法。首先利用方向波数的空间稀疏性,建立过完备稀疏字典,然后利用压缩采样阵列结构通过求解最优化问题得到方向波数的高分辨估计,最后利用最优空域滤波实现信号到达角度和频率的配对。相对于传统算法,该算法能够实现多信号DOA的高分辨估计,且经过压缩采样后降低了运算量,仿真验证了该算法的正确性与有效性。     

基于稀疏表示和近似l_0范数约束的宽带信号DOA估计

针对宽带信号的波达方向(DOA)估计问题,在稀疏框架下提出一种近似l_0范数约束的宽带信号DOA估计新算法。首先对宽带信号进行预处理,得到同一参考频率点下的接收数据,然后对其协方差矩阵元素进行加和平均运算,得到一个低维的观测向量,并在稀疏框架下进行稀疏表示,最后利用截断l_1函数设定权值,构造逼近l_0范数约束的稀疏重构方法,进而重构信号,获得宽带信号的DOA估计。仿真结果表明,相比于传统的宽带信号DOA估计算法,所提算法具有更高的分辨率和估计精度。     

基于改进TLS-ESPRIT算法的相干定位信号波达方向空间平滑

针对室内角度定位,在定位信号相干条件下无法实现准确估计波达方向(DOA)的问题,提出了一种基于TLS-ESPRIT算法的双向空间平滑方法。该算法先对定位相干信号进行双向空间平滑处理,然后用TLS-ESPRIT算法进行DOA的精确估计,使其最大限度地利用信号子空间的信息,从而解决了算法计算过程中输出信号的协方差矩阵秩亏损情况。该算法能够准确实现定位信号相干条件下DOA估计,与传统的空间平滑结合其他改进ESPRIT算法相比,具有更好的平稳性及抗干扰能力。最后通过仿真实验验证了算法的有效性和稳定性。     

存在阵列模型误差情况下的宽带DOA估计

 针对工程应用中存在阵列模型误差的任意形状天线阵列的宽带波达方向（DOA）估计问题,提出一种基于信号分离的相关域宽带松弛（RELAX）算法。此算法利用具有记忆与遗忘特征的矩阵算子的投影机理对入射信号进行有效的分离,因此对一定范围内的阵列模型误差较之基于子空间理论的传统宽带测向算法具有较好的鲁棒性与良好的工程应用前景。分析并证明了此算法的信号分离机理及此算法对阵列模型误差稳健的原理。理论分析与仿真结果均表明存在阵列模型误差时此算法宽带DOA估计的有效性和稳健性。     

DOA estimation under unknown mutual coupling and multipath

We propose a new method for direction of arrival (DOA) estimation in the presence of multipath propagation and mutual coupling for a frequency hopping (FH) system. With the use of pilot symbols and assuming perfect time-frequency synchronization for a linear array, we take mutual coupling and multipath propagation into account, and derive a maximum likelihood (ML) estimator for both the mutual coupling matrix and DOA estimation. We then formulate an iterative alternating minimization (AM) algorithm for finding the mutual coupling and DOA parameters in an alternate manner. Simulation results illustrating the performance of the algorithm and comparison with the Cramer-Rao bound (CRB) are also presented.     

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

Aiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.     

基于迭代QR分解的DOA估计技术

提出了一种基于迭代QR分解的信源到达角(DOA)估计技术.DOA估计的子空间方法主要是通过估计信号协方差矩阵的信号子空间或者噪声子空间来求出信号的DOA参数.估计这些子空间通常需要大量的计算,采用ASIC实现时其成本会非常昂贵.本文采用迭代QR分解方法进行子空间分解,可以利用较少量的计算资源完成处理任务.仿真实验结果达到0.23毫弧度,说明该算法比较可靠有效.     

DOA estimation for attitude determination on communication satellites

In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival （DOA） estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system （GPS） attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit （LEO） satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio （SNR） with DOA estimation.     

WiMAX dynamnic beamforming antenna

This presents our design and development of an 8-channel adaptive beaniforming antenna for new developments in radio technology: the emergence of chip-based components implementing the recently completed IEEE 802.16d-2004 (WiMAX) radio standard [1-4]. WiMAX offers the potential of long-range (up to 50 miles) and high bandwidth (up to 50 Mb~s) radio links. Although the new WiMAX standard offers the potential for using smart, adaptive antennas, this functionality has not been implemented. Our design will serve as a common platform for testing adaptive array algorithms including direction of arrival (DOA) estimation, beamforming, and adaptive tracking, as well as complete wireless communication with a WiMAX Radio. Heavy emphasis will be placed on ease of implementation in a multi-channel / multi-user environment. In the future, we hope to expand this interface to support dynamic radio channel selection via direct interaction with radio hardware or implementation of a cognitive radio system.     

Synchronized perturbation elimination and DOA estimation via signal selection mechanism and parallel deep capsule networks in multipath environment

State-of-the-art model-driven Direction-Of-Arrival (DOA) estimation methods for multipath signals face great challenges in practical application because of the dependence on the precise multipath model. In this paper, we introduce a framework, based on deep learning, for synchronizing perturbation auto-elimination with effective DOA estimation in multipath environment. Firstly, a signal selection mechanism is introduced to roughly locate specific signals to spatial subregion via frequency domain filters and compressive sensing-based method. Then, we set the mean of the correlation matrix’s row vectors as the input feature to construct the spatial spectrum by the corresponding single network within the parallel deep capsule networks. The proposed method enhances the generalization capability to untrained scenarios and the adaptability to non-ideal conditions, e.g., lower SNRs, smaller snapshots, unknown reflection coefficients and perturbational steering vectors, which make up for the defects of the previous model-driven methods. Simulations are carried out to demonstrate the superiority of the proposed method.     

直达与非直达环境中的多目标解耦直接定位方法

针对直达（LOS）与非直达（NLOS）环境中的定位问题,提出了一种波形已知条件下的单阵地多目标直接定位（DPD）算法。该算法针对发射时间已知和未知两种情况,利用多径信号到达角度与时延关于障碍物（或反射体）、观测站与目标位置参数的数学关系,建立了三维目标位置的最大似然（ML）函数,无需估计测量参数,避免了传统两步定位方法所需的非直达径识别与数据关联。为了克服多目标定位中的高维非线性优化问题,该算法利用独立波形信息将多目标定位解耦为对各个目标单独求解。通过对目标函数有效近似,算法在发射时间已知和未知两种情况下均仅需三维网格搜索,比相应的两步定位方法具有更低的计算量。此外,基于多径定位场景,推导了发射时间已知和未知两种情况下的位置估计克拉美罗界（CRB）。仿真结果表明：算法的定位性能能够逼近相应的克拉美罗界,比传统两步定位方法和子空间直接定位算法具有更高的定位精度。