Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,a...Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.展开更多
受恶劣电磁环境和元器件老化等因素影响,多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的天线阵元发生故障的概率增加,而阵元故障会严重降低目标波达方向(Direction of Arrival,DOA)估计性能。现有的大多数基于深度学习的DOA...受恶劣电磁环境和元器件老化等因素影响,多输入多输出(Multiple-Input Multiple-Output,MIMO)雷达的天线阵元发生故障的概率增加,而阵元故障会严重降低目标波达方向(Direction of Arrival,DOA)估计性能。现有的大多数基于深度学习的DOA估计方法未能充分利用阵列模型的先验信息,导致其建立的映射关系极为复杂,从而使得网络拟合难度较大。为此,提出一种基于先验驱动残差注意力网络的阵元故障MIMO雷达DOA估计方法。首先,利用MIMO雷达协方差矩阵的双重Toeplitz先验特性,构建了基于先验驱动的残差注意力网络,并引入残差注意力块对协方差矩阵的特征进行加权处理,旨在学习阵元故障下存在数据缺失的协方差矩阵和完整协方差矩阵生成向量之间的映射关系。然后,根据残差注意力网络输出的生成向量估计值得到完整的协方差矩阵。最后,利用RD-ESPRIT(Reduced Dimension ESPRIT)算法估计目标DOA。仿真结果表明,所提算法在阵元故障下的DOA估计性能优于现有算法,在信噪比为15 dB时,其DOA估计精度比效果最好的现有算法提高了43.26%。展开更多
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
为提高频控阵-多输入多输出(frequency diverse array multiple-input and multiple-output,FDA-MIMO)雷达系统的抗干扰能力,提出一种基于双子脉冲模式的FDA-MIMO雷达接收滤波器-发射频偏联合优化设计方法。在传统脉冲的基础上,引入双...为提高频控阵-多输入多输出(frequency diverse array multiple-input and multiple-output,FDA-MIMO)雷达系统的抗干扰能力,提出一种基于双子脉冲模式的FDA-MIMO雷达接收滤波器-发射频偏联合优化设计方法。在传统脉冲的基础上,引入双子脉冲发射模式并建立相关信号模型。在此基础上,建立以最大信干噪比(signal-to-interference-plus-noise ratio,SINR)为准则的接收滤波器-发射频偏联合优化问题。为了得到最优的接收-发射滤波器设计方案,引入一种迭代优化算法,将该优化问题拆分为接收滤波器优化和发射频偏优化两个独立的子问题。为进一步完成对发射频偏的设计,将其转化为关于发射导向矢量的设计问题,采用半正定松弛和随机方法,并通过发射导向矢量和频偏的数学关系获得频偏的最终设计方案。最后,通过仿真实验验证了所提双子脉冲FDA-MIMO雷达模式和接收滤波器-发射频偏联合优化设计方法对提高雷达系统抗干扰能力的有效性。展开更多
针对频控阵多输入多输出(frequency diverse array multiple-input multiple-output,FDA-MIMO)雷达在目标定位过程中存在的角度和距离耦合问题,提出两种低复杂度角度-距离超分辨估计算法,即二维求根(two-dimensional rooting,2D-root)...针对频控阵多输入多输出(frequency diverse array multiple-input multiple-output,FDA-MIMO)雷达在目标定位过程中存在的角度和距离耦合问题,提出两种低复杂度角度-距离超分辨估计算法,即二维求根(two-dimensional rooting,2D-root)算法和重构旋转不变子空间(reduced dimensional estimation of signal parameters via rotational invariance techniques,RD-ESPRIT)算法。首先,提出角度-距离二维谱重构方法,将二维参数谱进行一维化等价剥离。区别于传统求根超分辨算法,2D-root算法利用矩阵化子空间求根方法,构造双重求根多项式,分别对角度和距离进行高精度估计及参数自动配对。同时,为了进一步减少求根运算的计算量,RD-ESPRIT算法利用重构后角度谱内在的线性关系,获得信号子空间的旋转不变性,从而实现目标角度的高效求解。计算机仿真实验结果表明,所提两种算法在降低传统搜索类目标定位算法复杂度的基础上,可提高参数估计精度。展开更多
多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI),实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差问题。针对该问题,文中提出一种基于距离分复用(RDM)MIMO OFDM雷达的目标参数估计方法...多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI),实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差问题。针对该问题,文中提出一种基于距离分复用(RDM)MIMO OFDM雷达的目标参数估计方法。首先,建立RDM MIMO OFDM雷达信号模型,获得发射端在距离维的正交波形,使得雷达接收机的天线孔径得到明显扩展,提升角度分辨率;其次,在距离-速度处理和角度估计之间,提出一种二值掩码方法分离不同发射波形,代替了传统的带通滤波器,同时抑制噪声干扰,改善成像质量;最后,仿真验证所提方法的正确性和有效性,结果表明,与ESI相比,所提方法可以有效去除距离依赖性的角度误差,提升成像分辨率和角度参数估计精度。展开更多
多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI)方式,实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差和距离模糊问题。针对该问题,提出了一种基于距离分复用(RDM)的MIMO OFDM雷达距离...多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI)方式,实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差和距离模糊问题。针对该问题,提出了一种基于距离分复用(RDM)的MIMO OFDM雷达距离和角度联合估计方法。首先,建立RDM MIMO OFDM雷达信号模型,获得发射端在距离维的正交波形,同时消除了距离依赖性的角度误差;其次,在距离-速度-角度成像处理中采用改进DFT,代替传统DFT实现多普勒估计和校正;此外,在某些发射天线上额外添加相位偏移,打破目标峰值在距离维的等间距分布特性,通过搜索目标峰值距离索引差来确定模糊数,从而求解距离模糊问题。仿真结果验证了所提方法的有效性。展开更多
基金supported by National Natural Science Foundation of China(U20B2070,62001091)Sichuan Science and Technology Program(2022YFS0531).
文摘Most of the existing non-line-of-sight(NLOS)localization methods depend on the layout information of the scene which is difficult to be obtained in advance in the practical application scenarios.To solve the problem,an NLOS target localization method in unknown L-shaped corridor based ultra-wideband(UWB)multiple-input multiple-output(MIMO)radar is proposed in this paper.Firstly,the multipath propagation model of Lshaped corridor is established.Then,the localization process is analyzed by the propagation characteristics of diffraction and reflection.Specifically,two different back-projection imaging processes are performed on the radar echo,and the positions of focus regions in the two images are extracted to generate candidate targets.Furthermore,the distances of propagation paths corresponding to each candidate target are calculated,and then the similarity between each candidate target and the target is evaluated by employing two matching factors.The locations of the targets and the width of the corridor are determined based on the matching rules.Finally,two experiments are carried out to demonstrate that the method can effectively obtain the target positions and unknown scene information even when partial paths are lost.
文摘双基地多输入多输出(Multiple-Input Multiple-Output, MIMO)雷达阵元故障会导致三阶观测张量中出现缺失切片数据,严重影响目标角度估计性能。为此,提出一种基于原子范数的阵元故障MIMO雷达差分共阵角度估计方法。首先,对MIMO雷达三阶观测张量进行PARAFAC分解得到收发阵列的不完整因子矩阵;然后,利用收发阵列的因子矩阵分别获得发射和接收差分共阵的导向矩阵,并利用差分共阵的冗余度对故障阵元缺失数据进行填充,从而得到等效虚拟收发阵列的虚拟因子矩阵;最后,为了填补等效虚拟阵列中的空洞,分别对等效虚拟收发阵列的虚拟因子矩阵建立原子范数约束下的低秩矩阵重构模型,并将其表述为半正定规划(Semi-definite Programming, SDP)问题,利用交替方向乘子法(Alternating Direction Method of Multipliers, ADMM)求解该矩阵重构模型。仿真结果表明,所提方法可以有效重构出不完整因子矩阵中的缺失数据,从而改善MIMO雷达阵元故障下的角度估计性能。
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.
文摘为提高频控阵-多输入多输出(frequency diverse array multiple-input and multiple-output,FDA-MIMO)雷达系统的抗干扰能力,提出一种基于双子脉冲模式的FDA-MIMO雷达接收滤波器-发射频偏联合优化设计方法。在传统脉冲的基础上,引入双子脉冲发射模式并建立相关信号模型。在此基础上,建立以最大信干噪比(signal-to-interference-plus-noise ratio,SINR)为准则的接收滤波器-发射频偏联合优化问题。为了得到最优的接收-发射滤波器设计方案,引入一种迭代优化算法,将该优化问题拆分为接收滤波器优化和发射频偏优化两个独立的子问题。为进一步完成对发射频偏的设计,将其转化为关于发射导向矢量的设计问题,采用半正定松弛和随机方法,并通过发射导向矢量和频偏的数学关系获得频偏的最终设计方案。最后,通过仿真实验验证了所提双子脉冲FDA-MIMO雷达模式和接收滤波器-发射频偏联合优化设计方法对提高雷达系统抗干扰能力的有效性。
文摘针对频控阵多输入多输出(frequency diverse array multiple-input multiple-output,FDA-MIMO)雷达在目标定位过程中存在的角度和距离耦合问题,提出两种低复杂度角度-距离超分辨估计算法,即二维求根(two-dimensional rooting,2D-root)算法和重构旋转不变子空间(reduced dimensional estimation of signal parameters via rotational invariance techniques,RD-ESPRIT)算法。首先,提出角度-距离二维谱重构方法,将二维参数谱进行一维化等价剥离。区别于传统求根超分辨算法,2D-root算法利用矩阵化子空间求根方法,构造双重求根多项式,分别对角度和距离进行高精度估计及参数自动配对。同时,为了进一步减少求根运算的计算量,RD-ESPRIT算法利用重构后角度谱内在的线性关系,获得信号子空间的旋转不变性,从而实现目标角度的高效求解。计算机仿真实验结果表明,所提两种算法在降低传统搜索类目标定位算法复杂度的基础上,可提高参数估计精度。
文摘多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI),实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差问题。针对该问题,文中提出一种基于距离分复用(RDM)MIMO OFDM雷达的目标参数估计方法。首先,建立RDM MIMO OFDM雷达信号模型,获得发射端在距离维的正交波形,使得雷达接收机的天线孔径得到明显扩展,提升角度分辨率;其次,在距离-速度处理和角度估计之间,提出一种二值掩码方法分离不同发射波形,代替了传统的带通滤波器,同时抑制噪声干扰,改善成像质量;最后,仿真验证所提方法的正确性和有效性,结果表明,与ESI相比,所提方法可以有效去除距离依赖性的角度误差,提升成像分辨率和角度参数估计精度。
文摘多输入多输出(MIMO)正交频分复用(OFDM)雷达通常采用等间距子载频交错(ESI)方式,实现不同发射天线信号在频域的正交。然而,ESI存在距离依赖性的角度误差和距离模糊问题。针对该问题,提出了一种基于距离分复用(RDM)的MIMO OFDM雷达距离和角度联合估计方法。首先,建立RDM MIMO OFDM雷达信号模型,获得发射端在距离维的正交波形,同时消除了距离依赖性的角度误差;其次,在距离-速度-角度成像处理中采用改进DFT,代替传统DFT实现多普勒估计和校正;此外,在某些发射天线上额外添加相位偏移,打破目标峰值在距离维的等间距分布特性,通过搜索目标峰值距离索引差来确定模糊数,从而求解距离模糊问题。仿真结果验证了所提方法的有效性。
