Combining GA and iterative MVDR for DOA estimation in space-time CDMA systems

This paper deals with direction-of-arrival (DOA) estimation of minimum variance distortionless response (MVDR) approach based on iterative searching technique for space-time code-division multiple access (CDMA) systems. It has been shown that the iterative searching technique is more likely to converge to a local maximum, causing errors in DOA estimation. In conjunction with a genetic algorithm for selecting initial search angle, an efficient approach is presented to achieve the advantages of iterative DOA estimation with fast convergence and less computational load over existing conventional spectral searching MVDR estimator. Simulation results are provided for illustrating the effectiveness of the proposed approach.     

不同信号的DOA估计算法比较

波达方向(Direct of Arrival,DOA)估计技术渐渐成为移动通信中的研究热点,当用户的信号方向未知时,可以根据经典算法多重信号分类(Multiple Signal Classification,MUSIC)和旋转不变技术信号参数估计(Estimating Signal Parameters Viarotational Invariance Techniques,ESPRIT)等方法估计信号DOA。针对不同的信号采取不同的算法分析。对窄带信号,从信噪比、阵元数、快拍数等不同情况下对TLS-ESPRIT算法和MUSIC算法进行了仿真实验,并比较了TLS-ESPRIT算法与MUSIC算法的DOA性能。对宽带信号,主要重点分析了基于非相干信号处理算法(Incoherent Signal-subspace Method,ISM)的两种改进的方法,对低信噪比子带赋予低权重或舍弃。通过仿真实验,证明了改进算法的优越性,同时对两种改进算法的使用场合作了简单的分析。     

宽带混合信号的快速DOA估计算法

针对均匀线列阵,在宽带混合信号(不相关和相干信号共存)情形下,提出了一种DOA快速估计新算法。利用阵列协方差矩阵的Hermitian性,通过酉变换将各频点的复数据矩阵映射为实矩阵,通过实值化的TOFS法先直接估计出宽带非相关信号的DOA;然后利用空间差分技术,在各个频点上得到只含相干信号的数据协方差矩阵;通过Toeplitz矩阵重构,在不降低阵列孔径的条件下,可实现相干信号的解相干,再利用实值TOFS法可得到相干信号的DOA。由于算法是并行分别对不相关和相干信号进行DOA估计,在信源过载(信号数大于阵元数)的情形下,算法依然有效,同时由于实值化,算法的计算复杂度较小。仿真结果验证了算法的有效性。     

基于快怕矩阵重构的宽带相关信号DOA估计

针对相关信号空间平滑算法中阵列孔径损失的问题,提出了一种有效的去相关算法.该算法将直接数据快拍及其共轭反置矩阵构造一新的矩阵,通过对原数据矩阵和新矩阵的协方差矩阵的奇异值分解,再采用MUSIC算法对相关信号进行DOA估计,没有阵列孔径损失.仿真实验通过与MMUSIC算法和ISM算法及CSM算法相比较,验证了该算法的有效性.     

ADSP21160实现CDMA信号波达方向估计

本文针对CDMA系统,提出使用DSP器件ADSP21160实现对感兴趣用户的波达方向和估计的算法。该算法是对传统MUSIC方法的推广与变形,克服了要求接收信号数小于阵元数的局限,算法运算量小,能有效估计CDMA信号的到达方向。     

基于前后相关阵的CDMA信号DOA估计及DSP实现

本文针对CDMA系统,提出使用DSP器件TMS320-C6701实现对CDMA信号的波达方向估计。该算法基于对解扩前后相关阵相减,去除了干扰相关阵是,然后使用传统MUSIC或ESPRIT算法进行DOA估计,克服了要求接收信号数小于阵元数的局限,能有效估计波达方向相差很小的多径信号的参数。     

基于二次迭代稀疏重构的跳频信号参数估计

为了解决现有参数估计方法中时频聚集性不强,低信噪比下估计精度不高问题,提出了一种基于二次迭代稀疏重构的跳频信号参数估计方法。根据跳频信号的时频稀疏性进行稀疏重构,获取信号的时频分布矩阵;通过分析时频分布矩阵的特点,对信号进行二次迭代稀疏重构,获取二次时频分布矩阵。为了提高在低信噪比下算法性能,采用二值形态学滤波对时频图进行处理,进而实现信号的良好参数估计。仿真结果表明:该算法能够有效地提高参数估计精度,在低信噪比下有良好的估计效果。     

基于前后相关阵的CDMA信号DOA估计及DSP实现

本文针对CDMA系统,提出使用DSP器件TMS320-C6701实现对CDMA信号的波达方向估计.该算法基于对解扩前后相关阵相减,去除了干扰相关阵是,然后使用传统MUSIC或ESPRIT算法进行DOA估计,克服了要求接收信号数小于阵元数的局限,能有效估计波达方向相差很小的多径信号的参数.     

Optimized DOA estimation for an array antenna

Abstract—In this paper, we propose a Direction-of-Arrival (DOA) estimation technique that allows application of the signal subspace method. In the case when interference signals are coherent to the desired signals, the performance of the subspace method is reduced remarkably. As a solution to this problem, the spatial smoothing method has been proposed and applied. With the orthogonal element in the weighted spatial smoothing method being the calculation process to realize the MUSIC method, which is the most frequently used subspace, it becomes more complex. In order to solve this problem, we maximize the performance of DOA estimation by assigning a weight vector, which is directly orthogonal to the signal subspace. In this paper we compare the efficiency of the proposed algorithm with a modified spatial smoothing method via simulation results. The text was submitted by the authors in English.     

Robust DOA estimation and target docking for mobile robots

Direction of arrival (DOA) guided automated target acquisition and docking system is proposed for mobile robots employing the dual-directional antenna system. The dual-directional antenna estimates the DOA of the signal of interest using the ratio of the signal strengths between two adjacent antennas. In practice, DOA estimation poses a significant technical challenge, since the RF signal is easily distorted by the environmental conditions. Therefore, the robot often loses its way in an electromagnetically disturbed environment. To cope with this problem, a robust DOA estimation algorithm is developed based on Kalman filtering. This algorithm allows the robot to reduce the potential error in the estimated DOA, and adjust the robot’s heading to the target transponder without needing to know the positions of current and previous measurements in a global coordinate system. The simulation and experiment results clearly demonstrate that the mobile robot equipped with the developed system is able to dock to a target transponder in an indoor environment partially occupied by obstacles.     

DSP实现CDMA信号波达方向与多径时延联合估计

本文针对CDMA系统,提出使用DSP器件ADSP21160实现对感兴趣用户的波达方向和多径时延进行联合估计的算法。该算法是对传统MUSIC方法的推广与变形,克服了要求接收信号数小于阵元数的局限,能有效估计时延不同、波达方向相差很小的多径信号的参数。     

DSP实现CDMA信号波达方向与多径时延联合估计

本文针对CDMA系统,提出使用DSP器件ADSP21160实现对感兴趣用户的波达方向和多径时延进行联合估计的算法.该算法是对传统MUSIC方法的推广与变形,克服了要求接收信号数小于阵元数的局限,能有效估计时延不同、波达方向相差很小的多径信号的参数.     

基于频域ICA的波达方向估计方法

为降低阵元数目和提高相干多径入射信号的波达方向(DOA)估计精度。提出了一种基于频域独立分量分析与波束零点形成相结合的DOA估计方法。该方法综合利用阵列结构信息和目标信号的统计独立特性,与常规算法相比,降低了算法对阵元数目和精度的依赖,并能实现对相干多径入射信号的DOA估计。计算机仿真结果表明,该算法具有少阵元、收敛快、误差小的特点。     

面向船载远程会议的麦克风阵列高精度DOA估计

随着船舶智能化水平提高,船载远程会议系统对提高应急处理能力、推进船岸一体化网络建设有重要意义,麦克风阵列是保证远程会议系统语音效果和支持多模态交互的重要语音前端。但船舶舱室狭小尺寸一方面导致只能采用小尺寸麦阵,另一方面小舱室导致的强混响以及嘈杂舱室噪声也使传统麦克风阵列算法性能严重下降。考虑船舶舱室复杂环境下小尺寸麦阵DOA估计场景,提出了一种轻量级Mask-DOA估计神经网络模型。该方法在DOA估计神经网络引入Mask算法降低噪声和混响的干扰,并提取增强后的GCC-PHAT作为网络特征,从而在小尺寸麦阵上实现高精度DOA估计。仿真和实验结果表明,所提出的Mask-DOA模型面对复杂的船舶舱室环境更鲁棒,泛化能力更强。     

用户行为与遗传算法相结合的用户兴趣获取

尽管已经有一些遗传算法被应用于获取用户兴趣,但如何帮助用户找到最符合用户兴趣的信息,仍然存在诸多问题。好的适应度函数对于改善获取用户兴趣的遗传算法是非常重要的。该文设计了一个新的用于获取用户兴趣的遗传算法的适应度函数,使用该函数的遗传算法有效地提高了获取用户兴趣的准确性,减轻了用户的负担。通过实验,验证了该算法的有效性和优越性。     

基于主分量分析的宽带DOA估计自聚焦算法

提出了一种基于主分量分析(PCA)的CSM类宽带DOA估计自聚焦算法,利用子空间投影变换将信号分离后应用PCA算法快速估计信号DOA,通过不断更新聚焦方向实现自聚焦.与已有算法相比,该算法不受DOA初始值的影响,有更好的聚焦精度.聚焦矩阵更新过程中无需再做奇异值分解,用PCA迭代算法替代特征分解过程,计算量小.仿真实验结果表明,该算法以较小的计算代价实现了较好的估计精度.     

Adaptive multiuser receiver with joint channel and time delay estimation of CDMA signals based on the square-root unscented filter

The paper discusses an adaptive multiuser receiver for CDMA systems in which the scaled unscented filter (SUF) and the square root unscented filter (SURF) are used for joint estimation and tracking of the code delays and multipath coefficients of the received CDMA signals. The proposed channel estimators are more near-far resistant than the conventional extended Kalman filter (EKF) and present lower complexity than the conventional particle filter (PF) based methods. To present meaningful performance measures, the modified Cramer–Rao lower bound (CRLB) and computational complexity metrics are derived for the proposed and existing channel estimators. Computer simulation results demonstrate the superior performance of the proposed channel estimators. The proposed estimators are also shown to exhibit lower complexity relative to the PF.     

Design of input signals for parameter estimation

The optimum energy-constrained and time-constrained input signal is obtained for estimating the parameters of a system. The output is corrupted by nonstationary, nonwhite additive observation noise, and the observation time is finite. The reproducing kernel Hilbert space formulation is used to obtain the parameter estimates and the error covariance matrix in terms of the input. The performance index, assumed to be a function of the error covariance matrix, is minimized by a variational procedure. A necessary condition for optimality is that the input satisfy a nonlinear Fredholm equation. An example estimates the gain of a single time constant system where the observation noise has an exponential autocorrelation function. For broadband noise, the optimum input is a portion of a sinusoid. For a noise bandwidth narrower than the system bandwidth, the optimum input switches sign as rapidly as possible, but near-optimum performance can be obtained with a relatively high frequency sinusoidal input.     

High-resolution DOA estimation based on independent noise component for correlated signal sources

In this article, a modified complex-valued FastICA algorithm is utilized to extract the specific feature of the Gaussian noise component from mixtures so that the estimated component is as independent as possible to the other non-Gaussian signal components. Once the noise basis vector is obtained, we can estimate direction of arrival by searching the array manifold for direction vectors, which are as orthogonal as possible to the estimated noise basis vector especially for highly correlated signals with closely spaced direction. Superior resolution capabilities achieved with the proposed method in comparison with the conventional multiple signal classification (MUSIC) method, the spatial smoothing MUSIC method, and the signal subspace scaled MUSIC method are shown by simulation results.