For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in ...For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.展开更多
The wide-band direction finding is one of hit and difficult task in array signal processing. This paper generalizes narrow-band deterministic maximum likelihood direction finding algorithm to the wideband case, and so...The wide-band direction finding is one of hit and difficult task in array signal processing. This paper generalizes narrow-band deterministic maximum likelihood direction finding algorithm to the wideband case, and so constructions an object function, then utilizes genetic algorithm for nonlinear global optimization. Direction of arrival is estimated without preprocessing of array data and so the algorithm eliminates the effect of pre-estimate on the final estimation. The algorithm is applied on uniform linear array and extensive simulation results prove the efficacy of the algorithm. In the process of simulation, we obtain the relation between estimation error and parameters of genetic algorithm.展开更多
The antenna geometry strategy for direction finding （DF） with multiple-input multiple-output （MIMO） radars is studied. One case, usually encountered is practical applications, is consi- dered. For a directional an...The antenna geometry strategy for direction finding （DF） with multiple-input multiple-output （MIMO） radars is studied. One case, usually encountered is practical applications, is consi- dered. For a directional antenna geometry with a prior direction, the trace-optimal （TO） criterion （minimizing the trace） on the av- erage Cramer-Rao bound （CRB） matrix is employed. A qualitative explanation for antenna geometry is provided, which is a combi- natorial optimization problem. In the numerical example section, it is shown that the antenna geometries, designed by the proposed strategy, outperform the representative DF antenna geometries.展开更多
为了提高旋转不变子空间(estimation of signal parameters via rotational invariance techniques,ESPRIT)算法的分辨力和测角精度,充分利用非零延迟相关函数中信号入射角度的信息,提出了基于延时相关处理的ESPRIT算法。根据所有阵列...为了提高旋转不变子空间(estimation of signal parameters via rotational invariance techniques,ESPRIT)算法的分辨力和测角精度,充分利用非零延迟相关函数中信号入射角度的信息,提出了基于延时相关处理的ESPRIT算法。根据所有阵列间延时相关信息,构造新的阵列输出矩阵,并且得到新的协方差矩阵。对新的协方差矩阵进行特征值分解得到特征向量,通过将特征向量划分得到含有入射角度信息的子阵,最终求得信源的入射角度。仿真结果表明,该算法的分辨力和测角精度均优于原ESPRIT算法,并且在小角度间距情况下也有较好的分辨性能。展开更多
基于最大非圆率非圆信号特点,提出一种实值张量旋转不变子空间(estimation signal parameters via rotational invariance techniques,ESPRIT)算法。首先,通过研究张量与矩阵之间的转化关系,将阵列接收数据矩阵推广到张量空间;然后,利...基于最大非圆率非圆信号特点,提出一种实值张量旋转不变子空间(estimation signal parameters via rotational invariance techniques,ESPRIT)算法。首先,通过研究张量与矩阵之间的转化关系,将阵列接收数据矩阵推广到张量空间;然后,利用欧拉公式将阵列接收数据张量转化成余弦与正弦数据张量,根据阵列维数将其分别在各维上加以拼接,并对拼接的实值数据张量做高阶奇异值分解,获取信号子空间;最后,通过构造选择矩阵和进行特征分解,来联合估计阵列各维相位差,实现波达方向估计。实验仿真结果表明,此算法具有良好的分辨力和测角精度。展开更多
基金This work was supported by the National Natural Science Foundation of China(62073093)the Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province(LBH-Q19098)+1 种基金the Heilongjiang Provincial Natural Science Foundation of China(LH2020F017)the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology.
文摘For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.
基金This project was supported by the Teaching and Research Award Programfor Outstanding Young Teachersin Higher Educa-tion Institutions of MOE (2001226) .
文摘The wide-band direction finding is one of hit and difficult task in array signal processing. This paper generalizes narrow-band deterministic maximum likelihood direction finding algorithm to the wideband case, and so constructions an object function, then utilizes genetic algorithm for nonlinear global optimization. Direction of arrival is estimated without preprocessing of array data and so the algorithm eliminates the effect of pre-estimate on the final estimation. The algorithm is applied on uniform linear array and extensive simulation results prove the efficacy of the algorithm. In the process of simulation, we obtain the relation between estimation error and parameters of genetic algorithm.
基金supported by the National Natural Science Foundation of China(6107211761302142)
文摘The antenna geometry strategy for direction finding （DF） with multiple-input multiple-output （MIMO） radars is studied. One case, usually encountered is practical applications, is consi- dered. For a directional antenna geometry with a prior direction, the trace-optimal （TO） criterion （minimizing the trace） on the av- erage Cramer-Rao bound （CRB） matrix is employed. A qualitative explanation for antenna geometry is provided, which is a combi- natorial optimization problem. In the numerical example section, it is shown that the antenna geometries, designed by the proposed strategy, outperform the representative DF antenna geometries.
文摘由于共形天线阵列流形的多极化特性(polarization diversity,PD),信源方位参数与极化状态的"耦合"是实现共形阵列天线波达方向(direction-of-arrival,DOA)估计的主要难点。针对柱面共形阵列天线的特点,建立了柱面共形阵列天线的导向矢量模型;通过合理的阵元排列结构设计,结合ESPRIT(esti mation of signalparameters via rotational invariance techniques)算法参数估计的特点,实现了信源极化状态与方位参数的去耦合,推导了ESPRIT算法多参数估计的参数配对方法,最终提出了柱面共形阵列天线盲极化DOA估计算法。计算机Monte Carlo仿真实验验证了所提算法的有效性。
文摘为了提高旋转不变子空间(estimation of signal parameters via rotational invariance techniques,ESPRIT)算法的分辨力和测角精度,充分利用非零延迟相关函数中信号入射角度的信息,提出了基于延时相关处理的ESPRIT算法。根据所有阵列间延时相关信息,构造新的阵列输出矩阵,并且得到新的协方差矩阵。对新的协方差矩阵进行特征值分解得到特征向量,通过将特征向量划分得到含有入射角度信息的子阵,最终求得信源的入射角度。仿真结果表明,该算法的分辨力和测角精度均优于原ESPRIT算法,并且在小角度间距情况下也有较好的分辨性能。
文摘基于最大非圆率非圆信号特点,提出一种实值张量旋转不变子空间(estimation signal parameters via rotational invariance techniques,ESPRIT)算法。首先,通过研究张量与矩阵之间的转化关系,将阵列接收数据矩阵推广到张量空间;然后,利用欧拉公式将阵列接收数据张量转化成余弦与正弦数据张量,根据阵列维数将其分别在各维上加以拼接,并对拼接的实值数据张量做高阶奇异值分解,获取信号子空间;最后,通过构造选择矩阵和进行特征分解,来联合估计阵列各维相位差,实现波达方向估计。实验仿真结果表明,此算法具有良好的分辨力和测角精度。
