A MATCHED FILTER BANK BASED DOA ESTIMATION FOR ASYNCHRONOUS MULTIPATH CDMA CHANNELS

In this paper, a Direction Of Arrival (DOA) estimation algorithm is proposed for multiuser signals through uplink asynchronous multipath Code Division Multiple Access (CDMA) channels. The algorithm is based directly on the correlation matrices of matched filter bank outputs of desired user‘s multipath signals and it does not require that the elements of base station antenna array outnumber the multipath signals, which is necessary for the conventional sub-space based direction-finding algorithm. Simulation results show that the proposed algorithm estimates the DOA of multipath signals effectively and acceptably. The proposed algorithm has the prominent advantages of low complexity, simpleness and practicality, which make it much more suitable for practical application.     

DOA estimation of wideband sources without estimating the number of sources

In this paper, we propose a new technique to estimate wideband source directions from the sensor snapshots without requiring to know the number of sources present in the scenario. This work is motivated by the fact that the existing model order estimation (number of sources) techniques for wideband source scenario are either inaccurate or computationally expensive. Direction-of-arrival (DOA) estimation is realized using a beamformer framework which imposes nulls in the spatial spectrum along the source directions. The null width along the frequency axis is widened by introducing a new data dependent term into the optimization problem, thus achieving wideband capability. Furthermore, the temporal processing of the data snapshots drastically reduces the number of snapshots required for wideband DOA estimation. The effectiveness of the proposed formulation is studied with simulated experiments.     

基于高阶累积量虚拟阵列扩展的DOA估计

该文提出了一种基于高阶累积量虚拟阵列扩展的DOA估计新方法。该方法基于高阶累积量孔径扩展的性质,由实际阵元的坐标与方向矢量直接计算出虚拟阵元的坐标与方向矢量,利用两种阵元的坐标之间的关系构造四阶或六阶协方差矩阵,运用MUSIC方法对非高斯独立信号源进行DOA估计。该方法在任意阵列的情况下,对非高斯独立信号源进行一维与二维DOA估计,均能准确地估计出多于实际阵元数目的方向角与仰角。实验表明,该方法简单、有效地扩展了阵列孔径,提高了阵列的空间分辨能力,有效地抑制了高斯噪声的干扰,降低了高阶累积量协方差矩阵的计算量。     

一种新的二维角度估计的高分辨算法

该文针对常规2维波达方向估计的高分辨算法运算量大和稳健性差等问题,提出了一种新的2维角度估计的高分辨方法。该方法首先建立基于范数约束的最优化问题的目标函数;然后用迭代算法沿均匀面阵接收数据的方位向求最小化目标函数的稀疏解,得到方位、俯仰角耦合的空间角频率,并分离信号;最后对每个分离的信号,沿面阵俯仰向求稀疏解,得到信号的俯仰角,进而求得对应的方位角。针对算法存在测角盲区的问题,提出了一种改进方法,通过求解空间2维稀疏解得到信号的2维角度。与传统的高分辨算法相比,该方法对信噪比和快拍数要求不高、无需特征值分解和多维搜索过程,具有较高的分辨力和极低的旁瓣电平。     

基于空频解耦的宽带DOA估计算法

宽带波达方向(DOA)估计是宽带阵列信号处理领域的热点问题,当宽带信号的距离分辨率与宽带孔径可比拟时,孔径渡越效应会成为影响宽带波达方向估计精确度的重要因素。基于宽带阵列信号在空域与频域间呈现线性耦合的特点,利用梯形变换进行解耦处理,并对解耦后数据相干积累进行 DOA估计。实验结果表明,通过对宽带孔径渡越效应的消除,宽带 DOA估计精确度显著提高。该算法具有较低的计算复杂度和较高的 DOA估计精确度,是一种有效的宽带 DOA估计算法。     

A novel approach for DOA estimation in unknown correlated noise fields

The key of the subspace-based Direction Of Arrival （DOA） estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel approach for the estimation of DOA in unknown correlated noise fields is proposed in this paper. The approach is based on the biorthogonality between a matrix and its Moore-Penrose pseudo inverse, and made no assumption on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and it can give a robust and precise estimation of signal subspace, so a precise estimation of DOA is obtained. Its performances are confirmed by computer simulation results.     

A subarray-synthesis based 2D DOA estimation method

In some satellite communications, we need to perform Direction Of Arrival （DOA） angle estimation under the restriction that the number of receivers is less than that of the array elements in an array antenna. To solve the conundrum, a method named subarray-synthesis-based Two-Dimensional DOA （2D DOA） angle estimation is proposed. In the method, firstly, the array antenna is divided into a series of subarray antennas based on the total number of receivers; secondly, the subarray antennas＇ output covariance matrices are estimated; thirdly, an equivalent covariance matrix is synthesized based on the subarray output covariance matrices; then 2D DOA estimation is performed. Monte Carlo simulations showed that the estimation method is effective.     

An improved DOA estimation algorithm for asynchronous multipath CDMA system

This paper proposes an improved Direction Of Arrival（DOA） estimation algorithm for asynchronous multipath Code Division Multiple Access（CDMA） system. The algorithm is based on the correlation matrices of outputs of decorrelator, which is a Multi-User Detection（MUD） approach, one of the key techniques for CDMA system. Through decorrelating processing, the desired user＇s mulipath signals can be resolved and all the other resolved multipath signal interference is eliminated. So the proposed algorithm is expected to perforln much better than algorithm such as that based directly on the Matched Filter（MF） bank outputs. Simulation results confirm this. While the improved algorithm performs better and better as Signal-to-Noise Ratio（SNR） increases, the performance of algorithm based directly on the MF bank outputs can not be improved.     

一种适用于异步DS-CDMA系统的低复杂度DOA估计算法

针对异步DSCDMA系统的多用户环境,该文提出了一种低复杂度的DOA估计算法。该算法首先去除多址干扰及噪声项的影响,并构造出一组包含有感兴趣信息的相关阵;然后采用传统的MUSIC算法即可从这些矩阵中准确地估计出各DOA信息。算法具有计算量小,估计精度高等优点。仿真实验验证了算法的有效性。     

基于噪声子空间解析形式的快速DOA估计算法

该文针对特殊的信号环境各辐射源信号均值相等且不为零,利用均匀线阵导向矢量的Vandermonde结构,推导出了噪声子空间的解析形式,并以此为基础提出了利用均匀线阵和稀疏平面阵的1维和2维DOA估计快速算法。该算法不需要计算接收数据的协方差矩阵,也不需要任何矩阵分解,因此计算量远小于传统的超分辨DOA估计,而且无论信号之间是否具有相干性,该方法有相同的估计性能。仿真实验表明,在噪声均值为零且快拍数足够的条件下,该方法的估计性能整体上与Root-MUSIC算法相当,而在信噪比较低时性能优于后者。     

线性电磁矢量阵列的空时极化平滑算法及相干源多参数估计

该文提出了一种基于线性电磁矢量阵列的空时极化平滑算法(STPSA),解决了相干信源的频率,2维波达方向和极化参数的联合估计问题。该算法通过对不同子阵和矢量传感器不同传感单元的测量数据及其相应延迟数据进行平滑,实现解相干预处理并抑制噪声干扰,然后利用传播算子方法得到相应的参数估计。与目前的算法相比,该文提出的算法能够同时实现相干信源的多个参数联合估计;无需通过奇异值或特征值分解提取信号/噪声子空间,也无须进行参数搜索,有较低的运算量;另外,算法能够通过增加相邻阵元的间隔来扩展阵列的有效孔径,改善估计性能,且无须进行参数去模糊处理。仿真结果验证了算法的有效性。     

Estimation of 2-D DOA using non-circular music method for Uniform Circular and Rectangular Arrays

This paper extends the Non-Circular MUltiple SIgnal Classification (MUSIC) (NC-MUSIC) method for the common array geometries including Uniform Circular Arrays (UCAs) and Uniform Rectangular Arrays (URAs), which enables the algorithm to estimate 2-D Direction Of Arrival (DOA). A comparison between UCAs and URAs of NC-MUSIC is made in this paper. The simulations show that the NC-MUSIC method doubles the maximum estimation number of standard MUSIC. Using non-circular signals, the performance of URAs is improved remarkably while the improvement of UCAs is not so significantly. Moreover, the influence of arrays structures on the NC-MUSIC method is dis-cussed.     

一种基于迭代自适应的离网格DOA估计方法

针对真实信源位置与字典网格不匹配导致波达角估计(DOA)误差过大的问题,该文提出一种基于修正迭代自适应(IAA)功率谱算法的离网格(Off-Grid)DOA估计方法(OGIAA)。该方法首先通过修正IAA方法得到信号功率谱,读出功率峰值的对应网格角度作为粗估计结果,再利用平方误差代价函数,将代价函数2阶泰勒展开并最小化得到初始偏移量,最后交替优化功率分量和偏移量,实现高精度的离网格DOA估计。理论分析和仿真结果表明,该方法实现过程简单,无正则化参数影响,能准确估计出偏移网格的信源角度,在高阵列自由度的非均匀阵列上也同样具备高估计精度。     

基于协方差矩阵重构的离网格DOA估计方法

针对稀疏表示模型中网格失配导致波达方向角(DOA)估计存在较大估计误差的问题,该文提出一种基于协方差矩阵重构的离网格(Off-Grid)DOA估计方法(OGCMR)。首先,将DOA与网格点之间偏移量包含进所构建接收数据空域离散稀疏表示模型;而后基于重构信号协方差矩阵建立关于DOA估计的稀疏表示凸优化问题;再构建采样协方差矩阵估计误差凸模型,并将此凸集显式包含进稀疏表示模型以改善稀疏信号重构性能;最后采用交替迭代方法求解所得联合优化问题以获得网格偏移参数及离网格DOA估计。数值仿真表明,与传统多重信号分类(MUSIC)、L1-SVD及基于稀疏和低秩恢复的稳健MVDR (SLRD-RMVDR)等估计算法相比,所提算法具有较好的角度分辨力以及较高的DOA估计精度。     

Simple and efficient space-time channel and DOA estimation techniques in TD-SCDMA systems

In this paper, a simple method is presented for multi-user space-time channel estimation in Time Division-Synchronized Code Division Multiple Access （TD-SCDMA） systems. The method is based on a specific midamble assignment strategy, which results in a cyclic Toeplitz midamble-matrix in the linear equation of the received data vectors. A Fast Fourier Transform （FFT）-based algorithm is used to obtain the estimate of the uplink multi-user space-time channels. Furthermore, the estimated space-time channel is applied to the identification of multi-paths for each user, and Direction Of Arrival （DOA） estimation for each path is carried out by using the extracted spatial signature vector. Aside from the simplicity in computation, the proposed direction of arrival estimation method can effectively resolve multi-paths regardless of the correlation and angle separations of the multi-paths.     

强约束优化降维MUSIC二维DOA估计

该文针对2维DOA估计运算量大的问题,提出一种改进的降维MUSIC(MRD-MUSIC)算法。MRD-MUSIC算法利用二次优化方法将2维DOA估计分解为两级1维DOA估计,从而大大降低了运算量。其中采用对优化函数直接求导的方式求解问题函数,使方向向量得到了较强约束,因此求解结果更加接近最优解。仿真实验验证了算法的正确性,角度估计运算效率高,无角度配对过程,且具有较高的成功率与精确度。     

A novel wideband DOA estimator based on Khatri-Rao subspace approach

A novel DOA estimation method for uncorrelated wideband sources named focusing Khatri-Rao subspace method (FKR) is proposed based on coherent signal-subspace method (CSM) and Khatri-Rao (KR) subspace. Compared with the conventional CSM that simply averages the covariance matrices of different frequency bins after focusing, FKR transforms the covariance matrices into a higher dimensional matrix through KR product. This method has three major advantages: (1) it achieves a higher resolution than CSM, (2) the root mean square error of DOA estimation from FKR is smaller than that of CSM when the initial angles are inaccurate and (3) it performs well even when the number of sensors is reduced to about half of the sources. The performance of the FKR method is demonstrated and analyzed through the computer simulations.     

An efficient DOA estimation method in multipath environment

An efficient direction of arrival (DOA) estimation method is proposed with uniform linear array (ULA) in multipath environment. By applying a transformation, we can convert a constructed complex matrix to a real one, and then utilize the real matrix combined with our proposed criterion to estimate the DOAs of uncorrelated signals. Afterwards, the contributions of uncorrelated signals are eliminated, and then several new matrices without the information of uncorrelated signals are constructed to resolve the remaining coherent signals. The proposed estimation method overcomes the shortcomings of the existing methods and has satisfactory performance. Simulation results confirm the theoretical analysis and show the effectiveness of the proposed method.     

脉冲噪声下基于相关熵的相干分布源DOA估计新方法

针对复杂电磁环境下被动无线监测定位问题,该文提出广义相关熵的概念,推导了广义相关熵的性质,用以抑制阵列输出信号中的脉冲噪声。为了实现脉冲噪声环境下相干分布源中心DOA和扩散角的联合估计,提出基于广义相关熵的DOA估计新方法,并证明了该方法的有界性。为进一步提升算法的鲁棒性,推导了一种仅依赖阵列输出信号的自适应核函数。仿真结果表明,该算法能够实现脉冲噪声环境下相干分布源参数的联合估计,相比已有算法,具有更高的估计精度和鲁棒性。     

基于极化敏感阵列均匀线阵的二维DOA估计

针对残缺电磁矢量传感器的极化敏感阵列多参数联合估计问题,该文提出一种基于正交偶极子的均匀线阵的2维波达方向(Direction-Of-Arrival, DOA)估计算法。首先,对极化敏感阵列的接收数据矢量的协方差矩阵进行特征分解,然后将信号子空间划分成4个子阵,根据旋转不变子空间(ESPRIT)算法分别求出其中1个子阵与其它3个子阵的相位差,再对不同子阵间的相位差进行配对,最后根据相位差求出信号的DOA估计和极化参数。由正交偶极子组成的均匀线阵使用极化MUSIC算法和传统ESPRIT算法无法进行2维DOA估计,该文提出的算法解决了这个问题,并且相较于极化MUISC算法降低了算法的复杂度。仿真结果验证了该文算法的有效性。