基于高阶统计的空间信号频率与二维到达方向估计

基于一个线性阵列、两个孤立阵元以及输出信号四阶累积量,本文提出了一种多个空间窄带信号频率、到达方位角和仰角估计方法.方法不仅使它们的估计无需谱峰搜索且自动配对,而且使阵列的阵元数大大减小,适合任意高斯噪声环境.计算机模拟结果证实了方法的可行性.     

用任意阵实现二维到达角和极化的联合估计

基于四阶累积量和ＥＳＰＲＩＴ算法提出一种新的任意高斯噪声环境上多个独立空间信号二维到达角和极化的联合估计方法。该算法的阵列由和坐标轴方向一致的偶极子对组成,各偶极子对的排列结构任意。计算机模拟结果证实了方法的可行性。     

时空欠采样宽频段信号频率和二维角估计方法

本文提出了一种时空欠采样宽频段(2~18GHz)信号频率、方位角和仰角三维参数估计方法.该方法采用均匀圆阵和阵元延时,可在时间欠采样条件下实现频率无模糊估计;在空间欠采样条件下,用整数搜索法实现方位角和仰角无模糊估计,且频率、方位角和仰角估计可自动配对.该方法不仅可用于二阶统计量阵元空间和DFT波束空间,而且还可用于四阶累积量,可在高斯白或色噪声背景下,估计非高斯信源的参数.在DFT波束空间、阵元数相同和最大孔径相当时,该方法方位角和仰角估计的方差比L阵方法的方差小1~2个数量级.仿真实验表明了算法的有效性.     

近场源距离、频率及到达角联合估计算法

本文提出了一种近场源距离、频率及到达角(DOA)三维参数联合估计算法.该算法不需谱峰搜索且各参数自动配对.由于算法使用了四阶累积量,所以适用于任意加性高斯噪声环境.     

频率、二维到达角和极化联合估计

在宽频段内多信号多参量联合估计已成为许多研究课题,例如,。未知辐射源识别,有效对消等等的重要研究内容,信号频率与二维到达角、二维到达角与极化的联合估计已开展研究,但信号频率二维到达角和极化联合估计的研究尚未见报导,本文提出了利用交叉偶极子平面阵和ＥＳＰＲＩＴ算法实现频率、二维到达角和极化联合估计的新方法,分析了算法结构,计算机模拟结果证实了算法的有效性。     

相干信号频率和到达角联合估计的算法

基于均匀圆阵和四阶累积量,提出了一种相干信号频率和到达角联合估计的新算法。首先,利用计算量较小的PRO-ESPRIT算法和beamspace-ESPRIT算法分别估计广义阵列响应矢量和信号的频率。然后,对广义阵列响应矢量进行模式空间变换,并利用改进的前后向线性预测方法估计出相干信号的到达角。该算法能在色噪声环境下,精确地估计出空间相干信号的频率和到达角,并且无需平滑技术和谱峰搜索,具有计算量小,参数自动配对的特点。计算机仿真结果验证了算法的有效性。     

信号的二维到达角和极化估计

本文论述了一种基于子空间方法的多信号二维到达角和极化参量的估计算法。该方法采用了交叉偶极子阵元组成的Ｌ型阵列，利用子阵输出信号数据矩阵中包含的信号空间的旋转不变性质，借助于矩阵方法求解出信号的二维到达角和极化参量的估计值，并自动进行参数的配对，仿真结果证实了该算法的有效性。     

基于四阶累积量的相干信号频率和二维到达角联合估计的新算法

该文提出了一种基于四阶累积量的相干信号频率和二维到达角联合估计的新算法-CTSS算法.CTSS算法利用双平行线阵的时空数据以及平滑技术构造了一个时空平滑矩阵,通过对其进行特征分解,并利用分解得到的特征值和特征矢量估计出空间相干信号的三维参数.在色噪声环境下,该算法能够精确地估计空间相干信号的三维参数,无需多维谱峰搜索,能实现信号三维参数的自动配对,并有效地解决了信源参数兼并问题.计算机仿真结果验证了算法的有效性.     

极化信号频率、二维到达角和极化参数的同时估计

本文研究基于标量传感器和/或空域完全伸展矢量传感器极化敏感时间双采样、空间欠采样阵列的多个宽频段窄带极化信号中心频率、二维波达方向和极化参数的同时估计问题。针对时、空多分辨采样数据,利用旋转不变参数估计方法分别估计出与信号频率有关的时间相位因子和对应的含有空间相位信息的所谓混合导向矢量。对估计出的信号时间相位因子的模和相角进行联合,获得模拟频率估计:利用混合导向矢量中还包含的与空间采样间隔无关的极化-角度相干结构信息去除方向余弦估计中的整周模糊并获得相应的极化参数估计。     

一种基于高阶累积量的信号频率和到达角联合估计算法

该文研究了一种基于高阶累积量的信号频率和二维到达角联合估计算法。在分析了数据模型和M.C.Dogan等人提出的算法VESPA之后,本文给出了PRO-ESPRIT方法求解的VESPA.这一方法继承了高阶累积量抑制色高斯噪声的能力以及阵列虚拟扩展能力,用M个阵元的阵列可以分辨M1个空间信号,同时还可以实现信号频率和到达角的联合估计。数值仿真结果证实了算法的有效性。     

A fast algorithm for joint two-dimensional direction of arrival and frequency estimation via hierarchical space–time decomposition

In this paper, we present a fast algorithm for joint estimation of the two-dimensional (2-D) directions of arrival (DOAs) and frequencies of the incoming signals in wireless communications using a hierarchical space–time decomposition (HSTD) technique. Based on the HSTD, the proposed algorithm makes use of a sequence of one-dimensional (1-D) Unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms to estimate these parameters alternatively in a hierarchical tree structure. Also, in between every other 1-D Unitary ESPRIT algorithm, a temporal filtering process or a spatial beamforming process is invoked to partition the incoming signals into finer groups stage by stage to enhance the estimation accuracy as well as to alleviate the contaminated noise. Furthermore, with such a tree-structured estimation scheme, the pairing of these parameters is automatically determined without extra computational overhead. Simulation results show that the new algorithm provides satisfactory performance but with drastically reduced computations compared with previous works.     

柱面共形阵列信源方位与极化状态的联合估计算法

针对柱面共形极化敏感阵列的结构特点建立了其导向矢量模型,以此为基础实现了信源方位与极化状态的联合估计。根据旋转不变子空间思想估计俯仰角和子空间原理、秩损理论,通过对阵列流形矩阵进行特定的形式变换,将其中隐含的信源方位信息与极化信息\     

TDD CDMA通信系统中二维角度、时延和极化参数的可分离估计方法

在研究一维角度、时延和极化联合估计(JADPE)方法基础上,提出一种多径信道下的二维角度、时延和极化参数联合估计方法.该方法将极化敏感阵列天线和TDD CDMA系统结合起来,研究了TDD CDMA系统多用户、多径情况下联合参数估计问题,有效实现了TDD CDMA系统二维角度/时延/极化参数的高分辨联合估计.该方法通过引...     

低信噪比下对称三角线性调频信号参数估计

低截获概率雷达的广泛应用导致电子侦察系统截获到的雷达信号大多处于低信噪比环境中。针对目前雷达信号参数估计算法在此环境中性能急剧下降,甚至失效的问题,提出一种基于多相滤波器组和高阶累积量联合处理的对称三角线性调频连续波信号参数估计算法。该算法利用多相滤波器组实现信号在频域上的快速均匀划分,对输出的每个子带信号进行三阶累积量对角切片的短时估计,有效抑制了高斯噪声的干扰,并经过包络检波后得到信号完整的时频矩阵,通过对时频图像进行Radon变换得到信号带宽、周期以及调频斜率的估计,频率曲线的提取得到信号起止频率的估计。仿真结果表明:方法在信噪比大于-12dB时的估计正确率较高。     

基于联合对角化的近场源参数估计

该文提出了一种基于联合对角化的近场源信号到达方向和距离的联合估计算法。首先利用二阶统计量构造白化矩阵,再基于阵列接收数据的高阶累积量矩阵的对角结构信息利用联合对角化方法估计近场信号的阵列方向矩阵,从而由阵列导向矢量联合估计信号源的到达方向和距离。与高阶ESPRIT方法相比,该方法能够提高阵元利用效率,同时不需要参数配对算法。计算机仿真实验证实了所给算法的有效性。     

Joint Doppler frequency, 2D-DOD and 2D-DOA estimation for bistatic MIMO radar in spatial coloured noise

In this paper, we address the problem of four-dimensional angle and Doppler frequency estimation for L-shaped bistatic multiple input multiple output radar in spatial coloured noise. A novel method of joint estimation of Doppler frequency, two-dimensional direction of departure and two-dimensional direction of arrival based on the propagator method is discussed. Utilising the cross-correlation matrix which is formed by the adjacent outputs of matched filter in the time domain, the special matrix is constructed to eliminate the influence of spatial coloured noise. The proposed algorithm provides lower computational complexity and has very close parameter estimation to the estimation of signal parameters via rotational invariance techniques algorithm and DOA-matrix algorithm in high signal-to-noise ratio and Cramér–Rao bound is given. Furthermore, multidimensional parameters can be automatically paired by this algorithm to avoid the performance degradation resulting from wrong pairing. Numerical simulation results demonstrate the effectiveness of the proposed method.     

Joint parameter estimation of DOD/DOA/polarization for bistatic MIMO radar

In the paper,polarization-sensitive array is exploited at the receiver of multiple input multiple output (MIMO) radar system,a novel method is proposed for joint estimation of direction of departure (DOD),direction of arrival (DOA) and polarization parameters for bistatic MIMO radars. A signal model of polarimetric MIMO radar is developed,and the multi-parameter estimation algorithm for target localization is described by exploiting polarization array processing and the invariance property in both transmitter array and receiver array. By making use of polarization diversity techniques,the proposed method has advantages over traditional localization algorithms for bistatic MIMO radar. Simulations show that the performance of DOD and DOA estimation is greatly enhanced when different states of polarization of echoes is fully utilized. Especially,when two targets are closely spaced and cannot be well separated in spatial domain,the estimation resolution of traditional algorithms will be greatly degraded. While the proposed algorithm can work well and achieve high-resolution identification and accurate localization of multiple targets.     

Joint angle and Doppler frequency estimation of coherent targets in monostatic MIMO radar

This paper discusses the problem of joint direction of arrival (DOA) and Doppler frequency estimation of coherent targets in a monostatic multiple-input multiple-output radar. In the proposed algorithm, we perform a reduced dimension (RD) transformation on the received signal first and then use forward spatial smoothing (FSS) technique to decorrelate the coherence and obtain joint estimation of DOA and Doppler frequency by exploiting the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. The joint estimated parameters of the proposed RD-FSS-ESPRIT are automatically paired. Compared with the conventional FSS-ESPRIT algorithm, our RD-FSS-ESPRIT algorithm has much lower complexity and better estimation performance of both DOA and frequency. The variance of the estimation error and the Cramer–Rao Bound of the DOA and frequency estimation are derived. Simulation results show the effectiveness and improvement of our algorithm.     

Joint data detection and channel estimation for coded and uncoded continuous phase modulation signals

The performance of decision‐directed approach for joint data detection and channel estimation for continuous phase modulation (CPM) signal is limited because of an inevitable decision delay, which results in a trade‐off between data detection and channel estimation. In this paper, a novel hard output demodulation that solves the conflict requirement on the decision delay by predicting the channel coefficients over a given observation interval through a Kalman filter is proposed for uncoded CPM signal. The prediction guarantees high channel tracking capability and meanwhile maintains the accuracy of data detection. The proposed hard output demodulator is further extended to design a soft‐input soft‐output demodulator for serially concatenated CPM signal, which allows iterative processing. The convergence behavior of the proposed iterative receiver is presented. Simulation results show that the proposed demodulators provide improved performance in terms of bit error rate over some existing algorithms. Copyright © 2014 John Wiley & Sons, Ltd.