基于聚焦矩阵的超宽带信号DOA估计

超宽带(UWB-Ultra Wide Bandwidth)通信技术是无线通信中的一个非常有发展前途的技术.基于频域模型的UWB到达角估计方法只能解决非相干源问题,因此提出了一种改进的估计方法.该方法通过构造聚焦矩阵来估计相干源问题.仿真结果表明,该方法有效易行.     

超宽带信号DOA的估计方法

对信号到达角(DOA)的估计是超宽带定位的关键技术之一.传统的到达角估计方法都基于窄带信号,已不能直接应用在超宽带场合,因此提出了一种基于频域模型的宽带子空间谱估计方法.仿真结果表明,该方法能准确估计超宽带信号的到达角.     

多径传播条件下宽带线性调频信号波达方向估计方法

针对信号出现多径传播情况时现有宽带信号波达方向（direction of arrival, DOA）估计方法性能下降的问题,提出了一种多径传播条件下宽带线性调频（chirp）信号波达方向估计方法,该方法将导向有效投影（steered effective projection, STEP）技术与宽带线性调频信号的时频特性相结合,对具有不同时频特性的信号分量进行分离,逐个处理,并以时频分布矩阵代替传统的协方差矩阵,从而构造有效噪声子空间,实现时域角度估计。本方法无需进行信号聚焦操作,因此理论上不受聚焦误差的影响。仿真结果验证了所提方法的有效性。      

Adaptive beamspace focusing for direction of arrival estimation of wideband signals

In this paper, we present an adaptive beamspace focusing technique for the direction of arrival (DOA) estimation of wideband signals. The proposed focusing scheme can perform coherent signal subspace transformation in the beamspace domain without preliminary DOA estimation or iteration. It can maintain low focusing error over a predefined sector-of-interest in the field-of-view (FOV) of the array while adaptively suppressing out-of-sector sources. The beamspace gain outside the sector-of-interest is controlled via additional constraints that provide robustness against moving or suddenly appearing out-of-sector sources. We formulate the adaptive beamspace design problem as a second-order cone program (SOCP) that can be solved efficiently using interior point methods. Numerical simulations are presented showing the superior performance of our approach compared to classical non-adaptive beamspace focusing techniques.     

Fast detection and DOA estimation of the unknown wideband signal sources

The direction of arrival (DOA) estimation analysis requires prior knowledge of frequency‐related information of the incident wideband signals, eg, center frequency and bandwidth, which are not available in many cases. This research is based on applications where DOA estimation of the wideband signal source is unknown, eg, in astronomy and unauthorized transmissions. Therefore, this paper has two major contributions. The first contribution is to identify the frequency spectrum of the wideband signals transmitted from an unknown source. The method use edge detection prestage to identify the frequency spectrum of the received signal. The second contribution is to estimate the DOA of the wideband signal at higher accuracy while keeping a minimum computational cost. The estimation of the DOAs was analyzed by measuring the orthogonal relationship between the signal and the noise subspaces of multiple frequency components of the sources. The introduced method utilizes subband as a reference frequency based on the extracted frequency‐related information rather than examining the complete incoming signal spectrum and exploits the spatial information of a few subbands. The introduced algorithm is implemented based on the well‐known method, test of orthogonality of projected subspaces (TOPS). Tests are conducted on a range of wideband signals with extreme values of signal‐to‐noise ratio (SNR). Considerable performance improvement is obtained.     

Nested planar array: configuration design,optimal array and DOA estimation

Nested array enables to enhance localisation resolution and achieve under-determined direction of arrival (DOA) estimation. In this paper, we improve the traditional nested planar array to achieve more degrees of freedom (DOFs) and better angle estimation performance. The closed-form expressions for sensor positions of the improved array are given and the optimal array configuration for largest available DOFs is derived. Meanwhile, a computationally efficient DOA estimation algorithm is proposed. Specifically, we utilise two dimensional Discrete Fourier Transform (2D DFT) method to obtain the coarse DOA estimates; Subsequently, we achieve the fine DOA estimates by 2D spatial smoothing multiple signals classification (SS-MUSIC) algorithm. The proposed algorithm enjoys the same estimation accuracy as SS-MUSIC algorithm but with lower complexity because the coarse DOA estimates enable to shrink the range of spectral search. In addition, estimation of the number of signals is not required by 2D DFT method. Extensive simulation results testify the effectiveness of the proposed algorithm.     

相干宽带线性调频信号的波达方向估计新方法

提出了一种相干宽带线性调频(LFM)信号的波达方向(DOA)估计新方法。该方法利用LFM信号在分数阶Fourier域上的解线调特性,构造出新的解线调域阵列数据模型,然后结合传统的矩阵重构解相干以及MUSIC算法实现相干LFM信号的DOA估计。若同时存在多组相干LFM信号入射,则首先在不同的能量聚集域上将各信号组分离,然后逐一进行各组内相干信号的DOA估计。该方法充分地挖掘了观测信号所包含的时频信息,增加了可检测的DOA数目,提高了分辨性能和抗噪声性能。此外,该方法无冗余阵元与孔径损失,且适用于任意流型阵列。仿真结果显示,在DOA估计的均方根误差(RMSE)相同时,与传统方法相比,本方法可获得8dB左右的信噪比增益。     

宽带DOA估计的类MUSIC波束形成算法

为了提高频域波束形成的宽带波达方向估计性能,提出了类MUSIC波束形成算法(MBM,MUSIC-like Beamfomfing Method).在频域将宽带信号划分为若干窄带信号,叠加各窄带的MBM算法的空间谱后其峰值对应角度即为宽带波达方向估计结果.MBM算法的主瓣宽度在不同分析频率下基本保持不变,计算量与常规波束...     

宽带光控阵多波束超分辨测向算法

为了解决多信号并存时多波束系统的测向问题,针对宽带光控阵幅度加权和时延控制的多波束形成方式,提出了一种宽带波束域超分辨测向算法。建立了宽带光控阵多波束数据模型,首先将接收数据变换到频域,进行频谱分析,然后选择较大信号频率分量分别进行超分辨谱估计,最后将各频点估计结果融合得到最终的估计值。分析了波束参数的选取,包括波束数目、波束间隔以及幅度加权方式对算法性能的影响。算法能够分辨同时达到多波束系统的多个信号,仿真实验验证了算法的有效性和正确性。      

基于波束域的子空间正交性测试宽带DOA估计方法研究

投影子空间正交性测试(Test of Orthogonality of Projected Subspace:TOPS)算法通过测试宽带信号各频率点上噪声子空间和信号子空间之间的正交性对目标方位进行到达角估计(DOA:direction-of-arrival)。此算法对参考频点上的信号子空间的估计依赖性较大,因此存在较多伪峰,低信噪比条件下性能差等缺点。针对该问题,提出一种基于波束域的宽带DOA估计方法。该方法通过将阵列接收信号转换到波束域,在波束域中利用信号带宽内各频率分量的波束域方向向量与噪声子空间之间的正交关系构造判决向量,根据判决向量搜索空间谱的极大值对应的角度进行DOA估计。该方法不需要进行角度预估,避免了TOPS算法中常出现的伪峰,降低了信噪比分辨门限,减少了计算量,具有较好的估计效果。将该方法分别运用到均匀圆阵和线阵上,通过仿真对比和海试实验数据的处理,证明了本文所提方法的有效性。      

Joint Estimation of TOA and DOA in IR‐UWB System Using Sparse Representation Framework

This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra‐wideband systems with a two‐antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter‐estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint‐estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.     

基于时频子空间分解的宽带线性调频信号DOA估计

针对具有时变方向向量的宽带线性调频信号,该文建立了基于短时Wigner-Ville分布(WVD)的空间时频分布矩阵,通过对各个空间时频矩阵的特征分解获得对应的信号子空间和噪声子空间,给出了基于时频子空间投影实现多个时频点综合估计信号DOA的算法。利用空间时频分布的前后向平滑解决了具有相同时频特性信号的均匀线阵DOA估计问题。算法不需要聚汇和插值等复杂的矩阵变换,精度较高,计算简便.仿真实验显示该算法性能显著优越于基于矩阵插值的宽带调频信号DOA估计算法.     

基于宽频带多基线阵列解模糊的波达角估计算法

针对宽频带电子信号侦测系统测向精度与解相位模糊能力这一矛盾问题,根据多基线测向原理,提出一种基于宽频带多基线阵列解模糊的波达角估计算法,并进行了仿真分析。结果表明,该方法可有效求解宽频带多基线阵列相位模糊,提高对目标在相位差测量精度不高情况下的测向精度。     

Computationally efficient DOA estimation for coprime linear array: a successive signal subspace fitting algorithm

ABSTRACT

In this paper, direction of arrival (DOA) estimation of multiple signals with coprime array is investigated and signal subspace fitting (SSF) method is linked to the coprime array, which achieves a better DOA estimation performance than the traditional uniform array. While the SSF method requires expensive computational cost in the case of multiple signals due to the multidimensional global angular searching, we propose a successive SSF (S-SSF) algorithm from a computationally efficient perspective. In the proposed algorithm, we employ rotational invariance and coprime property to obtain the initial estimates. Then, via a successive scheme, we transform the traditional multidimensional global angular searching problem into one-dimensional partial angular searching one. Consequently, the computational complexity has been significantly reduced. Specifically, the proposed S-SSF algorithm can obtain almost the same DOA estimation performance as SSF but with remarkably lower complexity. Finally, Cramer-Rao Bound (CRB) is provided and numerical simulations demonstrate the effectiveness of the proposed algorithm.     

Direction of arrival estimation using adaptive directional time-frequency distributions

Time-frequency distributions (TFDs) allow direction of arrival (DOA) estimation algorithms to be used in scenarios when the total number of sources are more than the number of sensors. The performance of such time–frequency (t–f) based DOA estimation algorithms depends on the resolution of the underlying TFD as a higher resolution TFD leads to better separation of sources in the t–f domain. This paper presents a novel DOA estimation algorithm that uses the adaptive directional t–f distribution (ADTFD) for the analysis of close signal components. The ADTFD optimizes the direction of kernel at each point in the t–f domain to obtain a clear t–f representation, which is then exploited for DOA estimation. Moreover, the proposed methodology can also be applied for DOA estimation of sparse signals. Experimental results indicate that the proposed DOA algorithm based on the ADTFD outperforms other fixed and adaptive kernel based DOA algorithms.     

宽带DOA估计的频域时延补偿算法

针对宽带波达方向（Direction of Arrival,DOA）估计中导向矢量的频率不一致问题,提出一种新算法.首先对搜索方向信号进行时延补偿,使其与法线方向信号具有相同的阵列时延特征,同时将其它方向信号当作噪声处理,然后计算子空间的正交性并将其作为该搜索方向上空间谱值,最后给出快速算法以降低运算量.由于滤波器的群时延值不能任意改变,采用频域方法实现时延补偿.新算法不需要预估信号源数目和DOA初值,且仿真结果表明：在信号源互不相关和功率谱密度分布平坦的前提下,新算法分辨率更高、估计误差更小.     

宽带信号源数目和DOA快速估计

宽带信号源数目估计与其波达方向（DOA）估计是紧密相连的。文章综合考虑信号源数目和DOA估计,从减少算法的运算量出发,提出了一种新的宽带信号源数目和DOA快速估计方法。该方法首先利用多级维纳滤波器（MSWF）算法来估计信号子空间,避免了特征分解方法估计信号子空间所需要的大运算量;然后基于信号子空间的旋转不变性,提出了一种新的宽带信号源数目估计快速算法;最后利用信号子空间的旋转不变性来估计DOA,避免了谱峰搜索所需要的大运算量。计算机仿真试验验证了此方法的有效性。     

时频干涉仪到达角估计性能分析

传统干涉仪测向是对单个脉冲信号测向的，对于多信号没有分辨能力，对于线性调频等时变频率信号也不能直接应用。本文提出了一种时频干涉仪算法以实现对宽带线性调频信号的到达角（DOA）估计；同时该算法可实现多信号分辨；讨论了通道误差对算法性能的影响；分析表明，通道增益不一致不会造成DOA估计错误，而通道时延的不一致将造成DOA估计错误；给出了通道时延误差校正算法，通过校正可实现DOA的正确估计；计算机仿真结果证实了分析的正确性。     

Semiblind channel estimation for pulse-based ultra-wideband wireless communication systems

This paper proposes an H/sub /spl infin// based semiblind channel estimation algorithm for pulse-based ultra-wideband (UWB) wireless communication systems. In the proposed scheme, sparsely inserted periodic pilot symbols are exploited to adapt to not only the time-varying channel fading and noise processes but to their changing statistics and potential external disturbances, such as interference. While the existing optimal filtering-based channel estimation schemes, which are optimized mostly for traditional narrowband or wideband systems, require a priori knowledge of the channel and noise statistics, the proposed scheme does not. By further making full use of the channel characteristics unique in UWB systems, the proposed method is thus especially useful for robust operation in the highly frequency-selective UWB indoor channels for which the channel statistics are environment-dependent, and the noise processes do not necessarily satisfy the white Gaussian distribution in the presence of potential narrowband and multiuser interferences. Performance gain of the proposed scheme over the least square method, an existing technique that could also be applied to UWB channels with unknown statistics, and the Wiener filter-based algorithm is also provided.     

一种分布式目标波达方向估计方法

本文提出一种在多径情况下,利用广义阵列流形的特点,通过求解矩阵的广义特征值分解,不用进行谱峰搜索或多维参数搜索,直接由广义特征值得到分布式目标波达方向（DOA）估计的方法。该方法的估计性能对信号源的分布特性优于MUSIC方法。