A direction-of-arrival （DOA） estimation algorithm based on direct data domain （D3） approach is presented. This method can accuracy estimate DOA using one snapshot modified data, called the temporal and spatial two...A direction-of-arrival （DOA） estimation algorithm based on direct data domain （D3） approach is presented. This method can accuracy estimate DOA using one snapshot modified data, called the temporal and spatial two-dimensional vector reconstruction （TSR） method. The key idea is to apply the D3 approach which can extract the signal of given frequency but null out other frequency signals in temporal domain. Then the spatial vector reconstruction processing is used to estimate the angle of the spatial coherent signal source based on extract signal data. Compared with the common temporal and spatial processing approach, the TSR method has a lower computational load, higher real-time performance, robustness and angular accuracy of DOA. The proposed algorithm can be directly applied to the phased array radar of coherent pulses. Simulation results demonstrate the performance of the proposed technique.展开更多
In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exp...In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.展开更多
A new direction-of-arrival （DOA） estimation algorithm for wideband sources is introduced, The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation tec...A new direction-of-arrival （DOA） estimation algorithm for wideband sources is introduced, The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation techniques. The narrowband high- resolution algorithm is then used to get the DOA estimation. This technique does not require any preliminary knowledge of DOA angles. Simulation results demonstrate the effectiveness of the method.展开更多
To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the ste...To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.展开更多
A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.Acc...A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.According to the different characters of covariance matrix and general steering vector of the array received source,a second order blind identification method is used to separate the sources,the mixing matrix could be obtained.From the mixing matrix,the type of the source is identified by using an amplitude criterion.And the direction of arrival for the array received source is estimated by using the matching pursuit algorithm from the vectors of the mixing matrix.Computer simulations validate the efficiency of the method.展开更多
This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of th...This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of the DCN are the major challenge.In our deep estimator framework,one DCN is used for spectrum estimation with quantization errors,and the remaining two DCNs are used to estimate quantization errors.We propose training our estimator using the spatial sampled covariance matrix directly as our deep estimator’s input without any feature extraction operation.Then,we reconstruct the original spatial spectrum from the spectrum estimate and quantization errors estimate.Also,the feasibility of the proposed deep estimator is analyzed in detail in this paper.Once the deep estimator is appropriately trained,it can recover the correlated signals’spatial spectrum fast and accurately.Simulation results show that our estimator performs well in both resolution and estimation error compared with the state-of-the-art algorithms.展开更多
A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated usi...A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated using the conventional spatial spectrum estimation method, then the noise and uncorrelated sources in Toeplitz structure are eliminated using differencing, finally by exploiting the property of oblique projection, the contributions of correlated sources are then eliminated from the covariance matrix and only the coherent sources remain. So the coherent sources can be estimated by the technique of modified spatial smoothing. The number of sources resolved by this approach can exceed the number of array elements without repeatedly estimating correlated sources. Simulation results demonstrate the effectiveness and efficiency of our proposed method.展开更多
It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but th...It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.展开更多
由于传统的欧式空间方法无法有效反映协方差矩阵之间的差异,而导致信息损失,为了解决这一问题,提出了一种基于詹森-布雷格曼洛格德特散度(Jensen-Bregman LogDet divergence)的阵列波达方向(Direction of Arrival,DOA)估计方法,将目标...由于传统的欧式空间方法无法有效反映协方差矩阵之间的差异,而导致信息损失,为了解决这一问题,提出了一种基于詹森-布雷格曼洛格德特散度(Jensen-Bregman LogDet divergence)的阵列波达方向(Direction of Arrival,DOA)估计方法,将目标方位估计问题转化为矩阵流形上两点间的几何距离问题,揭示了方位估计与黎曼空间矩阵流形的映射规律,从而得到了几何距离最小值处对应的角度即为目标入射角度的结论,并通过构建两个强鲁棒性的矩阵流形,完成了矩阵信息几何DOA估计理论模型的建立。通过模拟仿真与实测数据对所新方法进行了验证。验证结果表明:与现有的最小方差无失真响应算法和多信号分类算法相比,新方法在低信噪比环境下拥有更好的估计精度;新方法的应用具有一定的实际意义和应用前景,可以为海洋防御及民用领域中的水下目标方位估计等提供坚实的技术支持。展开更多
互质阵列因具有较低的互耦效应而备受关注,但交替部署的子阵却在一定程度上限制了连续自由度的提升。针对上述问题,该文在分析子阵互差集中冗余虚拟阵元产生条件的基础上,提出了两种子阵移位互质阵列(Coprime Array with Translated Sub...互质阵列因具有较低的互耦效应而备受关注,但交替部署的子阵却在一定程度上限制了连续自由度的提升。针对上述问题,该文在分析子阵互差集中冗余虚拟阵元产生条件的基础上,提出了两种子阵移位互质阵列(Coprime Array with Translated Subarray,CATrS),以改善自由度性能。首先,将子阵平移至适当位置以优化布阵结构,并分析了子阵的平移距离。随后,推导了CATrS结构的自由度、连续自由度、孔洞位置和虚拟阵元权重的闭合表达式。理论分析表明,CATrS结构能够在保持物理阵元数量不变的条件下,有效增加自由度和连续自由度,并抑制阵元互耦。最后,利用仿真实验验证了CATrS结构在波达方向估计中的优越性。展开更多
针对互耦效应和脉冲噪声并存环境下的波达方向(direction of arrival,DOA)估计问题,提出一种结合M估计与稀疏重构的算法。首先,为了消除互耦效应的影响,依据互耦矩阵的托普利兹结构进行恒等变形,得到了不含未知互耦系数的字典。随后,为...针对互耦效应和脉冲噪声并存环境下的波达方向(direction of arrival,DOA)估计问题,提出一种结合M估计与稀疏重构的算法。首先,为了消除互耦效应的影响,依据互耦矩阵的托普利兹结构进行恒等变形,得到了不含未知互耦系数的字典。随后,为了使算法能适应高斯噪声和不同强度的脉冲噪声,将位置得分函数表示为高斯位置得分函数和一系列非线性函数的线性组合,利用噪声样本估计线性组合系数从而建立损失函数。最后,采用迭代硬阈值算法进行稀疏重构,并通过改进信号更新策略提高正确收敛的概率。仿真结果表明,所提算法能有效抑制互耦效应和脉冲(高斯)噪声的干扰,同时相较已有算法在低信噪比、强脉冲特性下的性能有显著提升。展开更多
针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法...针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法的思想对稀疏信号进行重构,得到信号在空域的稀疏系数矩阵;最后,将稀疏矩阵行向量的l2-范数映射到空域网格上,得到准确的DOA估计值.仿真实验结果表明:在低信噪比、小快拍、多信源条件下,该方法优于子空间类算法、贪婪类算法以及凸优化类算法,具有更低的均方根误差(RMSE)、更高的DOA估计精度和运行效率.展开更多
文摘A direction-of-arrival （DOA） estimation algorithm based on direct data domain （D3） approach is presented. This method can accuracy estimate DOA using one snapshot modified data, called the temporal and spatial two-dimensional vector reconstruction （TSR） method. The key idea is to apply the D3 approach which can extract the signal of given frequency but null out other frequency signals in temporal domain. Then the spatial vector reconstruction processing is used to estimate the angle of the spatial coherent signal source based on extract signal data. Compared with the common temporal and spatial processing approach, the TSR method has a lower computational load, higher real-time performance, robustness and angular accuracy of DOA. The proposed algorithm can be directly applied to the phased array radar of coherent pulses. Simulation results demonstrate the performance of the proposed technique.
基金supported by the National Natural Science Foundation of China(61571149)the Natural Science Foundation of Heilongjiang Province(LH2020F017)+1 种基金the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Heilongjiang Province Key Laboratory of High Accuracy Satellite Navigation and Marine Application Laboratory(HKL-2020-Y01).
文摘In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.
文摘A new direction-of-arrival （DOA） estimation algorithm for wideband sources is introduced, The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation techniques. The narrowband high- resolution algorithm is then used to get the DOA estimation. This technique does not require any preliminary knowledge of DOA angles. Simulation results demonstrate the effectiveness of the method.
文摘To enhance direction of arrival(DOA)estimation accuracy,this paper proposes a low-cost method for calibrating farfield steering vectors of large aperture millimeter wave radar(mmWR).To this end,we first derive the steering vectors with amplitude and phase errors,assuming that mmWR works in the time-sharing mode.Then,approximate relationship between the near-field calibration steering vector and the far-field calibration steering vector is analyzed,which is used to accomplish the mapping between the two of them.Finally,simulation results verify that the proposed method can effectively improve the angle measurement accuracy of mmWR with existing amplitude and phase errors.
文摘A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.According to the different characters of covariance matrix and general steering vector of the array received source,a second order blind identification method is used to separate the sources,the mixing matrix could be obtained.From the mixing matrix,the type of the source is identified by using an amplitude criterion.And the direction of arrival for the array received source is estimated by using the matching pursuit algorithm from the vectors of the mixing matrix.Computer simulations validate the efficiency of the method.
文摘This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of the DCN are the major challenge.In our deep estimator framework,one DCN is used for spectrum estimation with quantization errors,and the remaining two DCNs are used to estimate quantization errors.We propose training our estimator using the spatial sampled covariance matrix directly as our deep estimator’s input without any feature extraction operation.Then,we reconstruct the original spatial spectrum from the spectrum estimate and quantization errors estimate.Also,the feasibility of the proposed deep estimator is analyzed in detail in this paper.Once the deep estimator is appropriately trained,it can recover the correlated signals’spatial spectrum fast and accurately.Simulation results show that our estimator performs well in both resolution and estimation error compared with the state-of-the-art algorithms.
基金supported by the National Natural Science Foundation of China(60601016).
文摘A novel direction of arrival （DOA） estimation method is proposed when uncorrelated, correlated, and coherent sources coexist under color noise field. The uncorrelated and correlated sources are firstly estimated using the conventional spatial spectrum estimation method, then the noise and uncorrelated sources in Toeplitz structure are eliminated using differencing, finally by exploiting the property of oblique projection, the contributions of correlated sources are then eliminated from the covariance matrix and only the coherent sources remain. So the coherent sources can be estimated by the technique of modified spatial smoothing. The number of sources resolved by this approach can exceed the number of array elements without repeatedly estimating correlated sources. Simulation results demonstrate the effectiveness and efficiency of our proposed method.
基金supported by the National Natural Science Foundation of China(61771367)the Science and Technology on Communication Networks Laboratory(6142104190204).
文摘It is always a challenging issue for radar systems to estimate the height of a low-angle target in the multipath propagation environment.The highly deterministic maximum likelihood estimator has a high accuracy,but the errors of the ground reflection coefficient and the reflecting surface height have serious influence on the method.In this paper,a robust es-timation method with less computation burden is proposed based on the compound reflection coefficient multipath model for low-angle targets.The compound reflection coefficient is es-timated from the received data of the array and then a one-di-mension generalized steering vector is constructed to estimate the target height.The algorithm is robust to the reflecting sur-face height error and the ground reflection coefficient error.Fi-nally,the experiment and simulation results demonstrate the validity of the proposed method.
文摘由于传统的欧式空间方法无法有效反映协方差矩阵之间的差异,而导致信息损失,为了解决这一问题,提出了一种基于詹森-布雷格曼洛格德特散度(Jensen-Bregman LogDet divergence)的阵列波达方向(Direction of Arrival,DOA)估计方法,将目标方位估计问题转化为矩阵流形上两点间的几何距离问题,揭示了方位估计与黎曼空间矩阵流形的映射规律,从而得到了几何距离最小值处对应的角度即为目标入射角度的结论,并通过构建两个强鲁棒性的矩阵流形,完成了矩阵信息几何DOA估计理论模型的建立。通过模拟仿真与实测数据对所新方法进行了验证。验证结果表明:与现有的最小方差无失真响应算法和多信号分类算法相比,新方法在低信噪比环境下拥有更好的估计精度;新方法的应用具有一定的实际意义和应用前景,可以为海洋防御及民用领域中的水下目标方位估计等提供坚实的技术支持。
文摘互质阵列因具有较低的互耦效应而备受关注,但交替部署的子阵却在一定程度上限制了连续自由度的提升。针对上述问题,该文在分析子阵互差集中冗余虚拟阵元产生条件的基础上,提出了两种子阵移位互质阵列(Coprime Array with Translated Subarray,CATrS),以改善自由度性能。首先,将子阵平移至适当位置以优化布阵结构,并分析了子阵的平移距离。随后,推导了CATrS结构的自由度、连续自由度、孔洞位置和虚拟阵元权重的闭合表达式。理论分析表明,CATrS结构能够在保持物理阵元数量不变的条件下,有效增加自由度和连续自由度,并抑制阵元互耦。最后,利用仿真实验验证了CATrS结构在波达方向估计中的优越性。
文摘针对互耦效应和脉冲噪声并存环境下的波达方向(direction of arrival,DOA)估计问题,提出一种结合M估计与稀疏重构的算法。首先,为了消除互耦效应的影响,依据互耦矩阵的托普利兹结构进行恒等变形,得到了不含未知互耦系数的字典。随后,为了使算法能适应高斯噪声和不同强度的脉冲噪声,将位置得分函数表示为高斯位置得分函数和一系列非线性函数的线性组合,利用噪声样本估计线性组合系数从而建立损失函数。最后,采用迭代硬阈值算法进行稀疏重构,并通过改进信号更新策略提高正确收敛的概率。仿真结果表明,所提算法能有效抑制互耦效应和脉冲(高斯)噪声的干扰,同时相较已有算法在低信噪比、强脉冲特性下的性能有显著提升。
文摘针对现有的波达方向(direction of arrival,DOA)估计方法在低信噪比、小快拍、多信源条件下估计精度较低的问题,提出一种基于并行坐标下降算法的DOA估计方法.首先,对空域等角度均匀划分,构造超完备冗余字典;其次,采用并行坐标下降算法的思想对稀疏信号进行重构,得到信号在空域的稀疏系数矩阵;最后,将稀疏矩阵行向量的l2-范数映射到空域网格上,得到准确的DOA估计值.仿真实验结果表明:在低信噪比、小快拍、多信源条件下,该方法优于子空间类算法、贪婪类算法以及凸优化类算法,具有更低的均方根误差(RMSE)、更高的DOA估计精度和运行效率.
