多元M阵列的二值结构光编码

在结构光三维(3D)重建系统中,编码模式用来解决 对应点匹配问题,将直接影响测量的精度、分辨率和 实时性。M阵列的结构光模式具有良好的子窗体特性,全局唯一。通过归纳结构光模式应遵 守的规则,利 用改进的拼片算法生成了大尺寸多元M阵列,具有2×2的子窗体特性 ,有8个阵列元素。提出符号选择 机制,采用多条件评判方法确定8个模式符号。用设计的符号代替M阵列元素,生成一种 新颖的分辨率 为1024的M阵列单 帧二值结构光模式,以减少模式的个数及规避 环境光的较强干扰。对生成的编码模式 进行的实验结果表明,利用解码算法可有效地提取生成的M阵列中的符号关键点 的信息,并实现3D目标重建,验证了本文编码模式的有效性。     

A Tree Structure One-Dimensional Based Algorithm for Estimating the Two-Dimensional Direction of Arrivals and Its Performance Analysis

A tree structure algorithm using one-dimensional (1D) multiple signal classification (MUSIC) algorithm is proposed to estimate the two-dimensional direction of arrivals (2D DOAs) of coherent signals impinging on a uniform rectangular array. The basic idea of the proposed algorithm is to successively apply several times of the 1D spatial smoothing MUSIC algorithm, in tree structure, to estimate the azimuth and the elevation angles independently. To optimally separate the receive signal, constrained spatial beamformers with adjustable null width are exploited in conjunction with the 1D spatial smoothing MUSIC algorithm to decompose the received signal into several signals each lead by its own 2D DOA. Performance analysis is provided to investigate the estimation bias caused by the residue signal propagating in the tree structure.     

An efficient prime-factor algorithm for the discrete cosinetransform and its hardware implementations

The prime-factor decomposition is a fast computational technique for many important digital signal processing operations, such as the convolution, the discrete Fourier transform, the discrete Hartley transform, and the discrete cosine transform (DCT). The authors present a new prime-factor algorithm for the DCT. They also design a prime-factor algorithm for the discrete sine transform based on the prime-factor DCT algorithm. Hardware implementations for the prime-factor DCT are also studied. They are especially interested in the hardware designs which are suitable for the VLSI implementations. They show three hardware designs for the prime-factor DCT, including a VLSI circuit fabricated directly according to the signal-flow graph, a linear systolic array, and a mesh-connected systolic array. These three designs show the trade-off between cost and performance. The methodology, which deals with general (N₁× N₂)-point DCTs, where N₁ and N₂ are mutually prime, is illustrated by converting a 15-point DCT problem into a (3×5)-point 2D DCT problem     

单快拍数据的分布式二维阵列测角方法研究

该文针对2维阵列波达方向估计问题,提出一种基于单快拍数据的分布式2维DOA估计算法。该算法首先利用每个子阵单元的单快拍数据进行2维Hankle矩阵构造;然后基于2维状态空间平衡法分别获得方位角和俯仰角子阵单元内DOA估计与子阵单元间DOA估计;最后通过解模糊算法获得方位角和俯仰角高精度无模糊DOA估计。该算法较好地解决了子阵单元内DOA估计和子阵单元间DOA估计之间的配对问题以及俯仰角和方位角之间配对问题,充分利用分布式阵列扩展阵列物理孔径特性;同时该算法可直接对相干信号和非相干信号进行处理。计算机仿真结果验证了所提算法的有效性。     

基于宽带均匀同心球阵列的低复杂度二维波达方向估计算法

该文提出一种基于宽带均匀同心球阵列(UCSA)的2维波达方向(2D-DOA)低复杂度估计算法.该方法将宽带UCSA输出信号转换为相位模式,并对其进行频率补偿,实现近似频率不变(FI)特性,从而降低宽带信号处理的计算复杂度.为了进一步降低2D-DOA估计的计算复杂度,该文提出基于FI-UCSA的降维多重信号分类(MUSI...     

基于任意麦克风阵列的声源二维DOA估计算法研究

对基于麦克风阵列的声源定位技术进行了研究,分析了基于麦克风阵列的远场信号模型,并结合子空间的方法推导出了声源二维(水平角和俯仰角)DOA估计——2D-MUSIC算法,该算法适用于任意拓扑结构的麦克风阵列。利用MATLAB仿真工具,对几种典型阵列结构进行了对比分析,提出了2种新型的三维麦克风阵列:均匀球面阵和三维均匀直线阵。仿真结果表明,提出的DOA估计算法在二维的均匀圆阵、三维的均匀球面阵和三维均匀直线阵中,均能得到较好的DOA估计效果。     

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.     

Computational integral imaging-based 3D digital watermarking scheme using cellular automata transform and maximum length cellular automata

A novel 3D watermarking algorithm by combining use of computational integral imaging (CII) and cellular automata transform (CAT) is proposed in this paper. In this proposed scheme, first, the original image signal is decomposed into three resolution levels by using the level-3 2D CAT, and meanwhile, the middle-frequency domains are obtained. Then, an elemental images (EIs) array is generated by recording the information of rays of light coming from an object through a pinhole array in the CII system. The EIs array is encrypted by linear maximum-length cellular automata as the encrypted watermark embedded into the CAT middle-frequency domains. Finally, the watermarked image is obtained by using the level-3 2D inverse CAT. To verify the usefulness of the proposed algorithm, we carry out the computational experiments and present the experimental results for various attacks. Experimental results show that this proposed watermarking system provides excellent results in unobtrusiveness and robustness.     

Two-dimensional DOA estimation for acoustic vector-sensor array using a successive MUSIC

This paper discusses the problem of two-dimensional (2D) direction of arrival (DOA) estimation for acoustic vector-sensor array, and derives a successive multiple signal classification (MUSIC) algorithm therein. The proposed algorithm obtains initial estimations of the azimuth and elevation angles obtained from the signal subspace, and uses successively one-dimensional local searches to achieve the joint estimation of 2D-DOA. The proposed algorithm, which requires the one-dimension local searches, can avoid the high computational cost within 2D-MUSIC algorithm. The proposed algorithm can obtain automatically-paired 2D-DOA estimation for acoustic vector-sensor array, and it has better DOA estimation performance than propagator method, estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Meanwhile, it has very close angle estimation to 2D-MUSIC algorithm. Furthermore, it is suitable for non-uniform linear arrays, works well for the sources with the same azimuth angle, and imposes less constraint on the sensor spacing, which does not have to be restricted within half-wavelength. We have also derived the mean-square error of DOA estimation of the proposed algorithm and the Cramer-Rao bound of DOA estimation. Simulation results verify the usefulness of the proposed algorithm.     

一种改进的二维离散极坐标Fourier变换快速算法

在雷达天线、图象配准、图象检索等领域内常常需要用极坐标表示二维数字信号的离散Fourier变换(DFT).与笛卡尔坐标系下的二维DFT不同,二维离散极坐标Fourier变换(DPFT)不具有行列可分性,直接计算非常耗时.本文提出一种改进的DPFT的快速算法.该算法针对二维阵列实信号,算法全部过程可用一维运算实现,大大降低了计算复杂度并且适用于实时处理.实验中与直接运算方法相比较,显示了该算法的良好性能.     

New 2D systolic array algorithm for DCT/DST

Presents an algorithm and the architecture of a 2D systolic array processor for the DCT (discrete cosine transform) and the DST (discrete sine transform). It is based on the IDFT (inverse discrete Fourier transform) version of the Goertzel algorithm via Horner's rule. This 2D systolic array for the DCT/DST can be met by achieving a systematic technique for transforming algorithms to specific forms for mapping onto 2D systolic arrays.<>     

一种基于平行稀疏阵列虚拟孔洞填充的二维DOA估计算法

采用稀疏阵列进行波达方向（Direction of Arrival,DOA）估计时往往会产生虚拟孔洞，它严重限制了阵列孔径的扩展与阵元自由度的提升。由于孔洞位置与初始阵列阵元数目、排布方式有关，故较难对其进行预填充。为此，提出了一种基于平行稀疏阵列虚拟孔洞填充的二维DOA估计算法，利用双稀疏线阵扩展生成两个不同的虚拟阵列，并利用其中一阵的信息去填充另一阵的孔洞。为尽可能减少总阵元数目，采用提前计算的孔洞位置去设计另一阵列的排布规则，并通过求根多重信号分类(Root-Mutiple Signal Classification，Root-MUSIC）算法替代传统的二维谱峰搜索算法完成对入射角度的估计与自动匹配。实验仿真结果验证了所提算法相比传统算法能以更少的阵元获得更高的估计精度。     

基于稀疏贝叶斯正则化的阵列SAR高分辨三维成像算法

阵列合成孔径雷达(Linear Array Synthetic Aperture Radar, LASAR) 3维成像技术是一种具有重要潜在应用价值的雷达成像新体制,但受线阵天线及平台尺寸限制,传统匹配滤波成像算法难以实现LASAR高分辨3维成像。该文利用LASAR回波信号及观测目标的先验分布特性,提出了一种基于快速稀疏贝叶斯正则化重构的LASAR高分辨3维成像算法。该算法先结合贝叶斯估计准则及最大似然估计原理,构造LASAR目标重构的稀疏贝叶斯最小化代价函数;再利用迭代正则化方法求解联合范数最优化问题实现LASAR稀疏目标高分辨3维成像。另外,针对稀疏贝叶斯正则化成像运算量大的问题,结合位置预测快速成像思路,利用阈值分割算法对稀疏粗成像进行强目标提取,进而提升算法运算效率。仿真数据和实测数据验证了该文算法的有效性。      

Unfolded coprime L-shaped arrays for two-dimensional direction of arrival estimation

Generally, a coprime L-shaped array (CLsA) is composed of two uniform L-shaped subarrays with larger spacing among inter-element to accomplish the improved direction of arrival (DOA) estimation performance. In this paper, the two subarrays are unfolded to extend the array aperture and the performance of the unfolded CLsA (UCLsA) for two-dimensional (2D) DOA estimation is investigated. In addition, an all array multiple signals classification (AA-MUSIC) algorithm is proposed for the UCLsA. By stacking the received signals of the two subarrays, the ambiguity problem can be avoided on the basis of the coprime property. Simultaneously, due to the combination of the cross-correlation and auto-correlation, the proposed AA-MUSIC algorithm can achieve the full degrees of freedom (DOFs) and obtain more accurate DOA estimates, nevertheless, the expensive total spectral search is entailed. Consequently, a reduced complexity MUSIC (RC-MUSIC) algorithm is proposed to relieve the computational burden. The Cramer-Rao Bounds (CRBs) are utilised as a theoretical benchmark for the lower bound of unbiased estimate. Furthermore, numerical simulations verify the effectiveness and superiority of the AA-MUSIC algorithm and RC-MUSIC method for the UCLsA.     

A wavelet technique applied to estimate image shifts and enhance image resolution during processing of a sequence of shifting digital frames

The problem of high-resolution image reconstruction from noisy frames that are received by a photodetector array and shifted with respect to each other is considered. A wavelet technique is proposed for solution of this problem. The technique uses a 2D wavelet decomposition as a parametric model of the brightness function of an image in the plane of the photodetector array. A recurrent-iteration algorithm is developed for combined estimation of variable frame shifts and of the coefficients of the wavelet docomposition corresponding to the doubly improved resolution. It is shown that, under various conditions, the algorithm provides for estimation of shifts with an error no greater than 0.06 of the array pitch and for estimation of an observed-object’s brightness function with a resolution twice as high as the input-frame resolution.     

基于Khatri-Rao积的三维前视声呐空间方位估计技术

为了提高3维前视声呐的方位分辨能力,同时避免2维(2D)方位估计(DOA)方法失效,该文提出1维(1D)空间角估计方法、基于Vernier法的垂直角估计方法和基于最小角定理的水平角方位估计方法。首先基于不同子阵构造互协方差矩阵避免2维方位估计模型失效,再利用Khatri-Rao积进行虚拟孔径扩展;将扩展后的阵列导向矢量和观测向量模型用于2维方位估计。与原阵列的导向矢量相比,虚拟阵元数量约增加1倍,阵列的孔径得到有效扩展。仿真实验表明,与单观测向量波束形成2维方位估计方法相比,所提方法在2维方位估计问题中具有更高的分辨能力,均方根误差更低;水池实验进一步验证了该文所提方法的工程实用性。     

Efficient 2D DOA estimation of coherent signals in spatially correlated noise using electromagnetic vector sensors

This paper considers a new azimuth-elevation DOA estimation algorithm for multiple signals using electromagnetic vector sensor array. We firstly exploit the planar-plus-an-isolated sensor array geometry (Li et al. in IEE Proc Radar Sonar Navig 143(5):295–299, 1996) to define a full rank cross-covariance matrix. Then we develop an efficient ESPRIT-like algorithm using the so-called propagator to estimate the steering vectors of electromagnetic vector sensor, without performing eigen-decomposition into signal subspaces. Finally, we compute the vector cross product to obtain the closed-form azimuth-elevation angle estimates. The new algorithm does not require 2D iterative searching, and is applicable to coherent (fully correlated) signals and spatially correlated noise. In addition, the proposed algorithm offers enhanced estimation precision by sparse array aperture extension, but suffers no DOA cyclical ambiguity. Monte-Carlo simulations are presented to verify the effectiveness of the proposed algorithm.     

基于秩减估计器的L型阵列二维波达角估计算法

针对L型阵列2维波达角(2D-DOA)估计问题,该文提出了一种新的基于秩减估计器的算法。该算法利用辅助角将2D-DOA估计问题转换为两个级联的1D-DOA估计问题:首先采用基于传播算子的秩减估计器获得高精度的辅助角估计;其次利用辅助角估计结果获得某一入射角的一元代价函数,借鉴root-MUSIC算法通过对多项式求根获得某一入射角估计,而另一入射角估计可由已得角度估计和辅助角估计通过简单转换获得且两入射角之间无需配对。运算量分析表明,该算法运算量与JEADE算法接近,大于CODE和root-MUSIC算法。仿真实验验证了该算法在不同信噪比、快拍数目条件下可获得高精度的DOA估计结果。     

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。     

基于能量收集的UAV-D2D网络资源分配算法

为更好地利用周围环境中的射频信号能量,提升终端直连(D2D)通信的运行时间和无人机(UAV)通信的频谱利用率,该文提出一种基于能量收集的UAV-D2D网络资源分配算法.考虑UAV最大发射功率和移动性约束,蜂窝用户和D2D用户的最小速率约束,建立了系统和速率最大化的多变量耦合资源分配问题.利用连续凸近似和变量替换方法将混...