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1. 发明授权

US08907841B2 Method for detecting targets using space-time adaptive processing 有权
标题翻译：使用空时自适应处理检测目标的方法
公开(公告)号：US08907841B2
公开(公告)日：2014-12-09
申请号：US13291323
申请日：2011-11-08
申请人： Zafer Sahinoglu , Man-On Pun , Pu Wang
发明人： Zafer Sahinoglu , Man-On Pun , Pu Wang
IPC分类号： G01S13/50 , G01S13/524 , G01S7/292 , G01S13/02
CPC分类号： G01S7/292 , G01S13/5244 , G01S2013/0245
摘要： A method for detecting a target in a non-homogeneous environment using a space-time adaptive processing of a radar signal includes normalizing training data of the non-homogeneous environment to produce normalized training data; determining a normalized sample covariance matrix representing the normalized training data; tracking a subspace represented by the normalized sample covariance matrix to produce a clutter subspace matrix; determining a test statistic representing a likelihood of a presence of the target in the radar signal based on the clutter subspace matrix and a steering vector; and comparing the test statistic with a threshold to detect the target.
摘要翻译：使用雷达信号的时空自适应处理来检测非均匀环境中的目标的方法包括对非均匀环境的训练数据进行归一化以产生归一化的训练数据; 确定表示归一化训练数据的归一化样本协方差矩阵; 跟踪由归一化样本协方差矩阵表示的子空间以产生杂波子空间矩阵; 基于所述杂波子空间矩阵和导向矢量，确定表示所述雷达信号中所述目标的存在的可能性的测试统计量; 并将检验统计与阈值进行比较以检测目标。

2. 发明授权

US08138963B1 Method for detecting targets using space-time adaptive processing and shared knowledge of the environment 有权
标题翻译：使用时空自适应处理和共享环境知识来检测目标的方法
公开(公告)号：US08138963B1
公开(公告)日：2012-03-20
申请号：US12879288
申请日：2010-09-10
申请人： Man-On Pun , Zafer Sahinoglu , Pu Wang
发明人： Man-On Pun , Zafer Sahinoglu , Pu Wang
IPC分类号： G01S13/00 , G01S13/08
CPC分类号： G01S7/292 , G01S13/04
摘要： A method detects a target in a radar signal using space-time adaptive processing. A test statistic is T = max α ⁢ max λ ⁢ ∫ R ⁢ f 1 ⁡ ( x 0 , x 1 , … ⁢ , x K ❘ α , λ , R ) ⁢ p ⁡ ( R ) ⁢ ⁢ ⅆ R max λ ⁢ ∫ R ⁢ f 0 ⁡ ( x 0 , x 1 , … ⁢ , x K ❘ λ , R ) ⁢ p ⁡ ( R ) ⁢ ⁢ ⅆ R , where x0 is a test signal, xk are K training signals, α is an unknown amplitude of a target signal within the test signal, λ is a scaling factor, R is a covariance matrix of the training signals, and a function max returns a maximum values. The test statistic is compared to a threshold to determine whether the target is present, or not.
摘要翻译：一种方法使用空时自适应处理来检测雷达信号中的目标。一个检验统计量是T = maxα⁢最大λ∫∫R f 1⁡（x 0，x 1，...，x K |α，λ，R）p⁡（R） ∫R f 0⁡（x 0，x 1，...，x K |λ，R）p⁡（R）⁢ⅆR，其中x0是测试信号，xk是K个训练信号，α是在测试信号内的目标信号的未知振幅，λ是比例因子，R是训练信号的协方差矩阵，函数max返回最大值。将测试统计量与阈值进行比较，以确定目标是否存在。

3. 发明授权

US08284098B2 Persymmetric parametric adaptive matched filters for detecting targets using space-time adaptive processing of radar signals 有权
标题翻译：用于使用雷达信号的空时自适应处理来检测目标的不对称参数自适应匹配滤波器
公开(公告)号：US08284098B2
公开(公告)日：2012-10-09
申请号：US12954254
申请日：2010-11-24
申请人： Zafer Sahinoglu , Pu Wang , Man-On Pun
发明人： Zafer Sahinoglu , Pu Wang , Man-On Pun
IPC分类号： G01S13/00
CPC分类号： G01S13/5244 , G01S13/5242
摘要： A method provides space-time adaptive processing (STAP) for target detection using adaptive matched filters (AMF). A generalized likelihood ratio test (GLRT) is determined where spatial and temporal correlation matrices Q and A are assumed. Then, the correlation matrices A and Q are replaced with maximum likelihood (ML) estimates obtained only from training signals subject to a persymmetric constraint.
摘要翻译：一种方法使用自适应匹配滤波器（AMF）提供用于目标检测的时空自适应处理（STAP）。在假定空间和时间相关矩阵Q和A的情况下确定广义似然比检验（GLRT）。然后，相关矩阵A和Q被替换为仅由经受不对称约束的训练信号获得的最大似然（ML）估计。

4. 发明申请

US20120249361A1 Method for Detecting Targets Using Space-Time Adaptive Processing 有权
标题翻译：使用时空自适应处理检测目标的方法
公开(公告)号：US20120249361A1
公开(公告)日：2012-10-04
申请号：US13291323
申请日：2011-11-08
申请人： Zafer Sahinoglu , Man-On Pun , Pu Wang
发明人： Zafer Sahinoglu , Man-On Pun , Pu Wang
IPC分类号： G01S13/04
CPC分类号： G01S7/292 , G01S13/5244 , G01S2013/0245
摘要： A method for detecting a target in a non-homogeneous environment using a space-time adaptive processing of a radar signal includes normalizing training data of the non-homogeneous environment to produce normalized training data; determining a normalized sample covariance matrix representing the normalized training data; tracking a subspace represented by the normalized sample covariance matrix to produce a clutter subspace matrix; determining a test statistic representing a likelihood of a presence of the target in the radar signal based on the clutter subspace matrix and a steering vector; and comparing the test statistic with a threshold to detect the target.
摘要翻译：使用雷达信号的时空自适应处理来检测非均匀环境中的目标的方法包括对非均匀环境的训练数据进行归一化以产生归一化的训练数据; 确定表示归一化训练数据的归一化样本协方差矩阵; 跟踪由归一化样本协方差矩阵表示的子空间以产生杂波子空间矩阵; 基于所述杂波子空间矩阵和导向矢量，确定表示所述雷达信号中所述目标的存在的可能性的测试统计量; 并将检验统计与阈值进行比较以检测目标。

5. 发明申请

US20120127027A1 Persymmetric Parametric Adaptive Matched Filters for Detecting Targets Using Space-Time Adaptive Processing of Radar Signals 有权
标题翻译：用于使用雷达信号的时空自适应处理来检测目标的非对称参数自适应匹配滤波器
公开(公告)号：US20120127027A1
公开(公告)日：2012-05-24
申请号：US12954254
申请日：2010-11-24
申请人： Zafer Sahinoglu , Pu Wang , Man-On Pun
发明人： Zafer Sahinoglu , Pu Wang , Man-On Pun
IPC分类号： G01S13/00
CPC分类号： G01S13/5244 , G01S13/5242
摘要： A method provides space-time adaptive processing (STAP) for target detection using adaptive matched filters (AMF). A generalized likelihood ratio test (GLRT) is determined where spatial and temporal correlation matrices Q and A are assumed. Then, the correlation matrices A and Q are replaced with maximum likelihood (ML) estimates obtained only from training signals subject to a persymmetric constraint.
摘要翻译：一种方法使用自适应匹配滤波器（AMF）提供用于目标检测的时空自适应处理（STAP）。在假定空间和时间相关矩阵Q和A的情况下确定广义似然比检验（GLRT）。然后，相关矩阵A和Q被替换为仅由经受不对称约束的训练信号获得的最大似然（ML）估计。

6. 发明申请

US20120062409A1 METHOD FOR DETECTING TARGETS USING SPACE-TIME ADAPTIVE PROCESSING AND SHARED KNOWLEDGE OF THE ENVIRONMENT 有权
标题翻译：使用空间自适应处理和共享环境知识来检测目标的方法
公开(公告)号：US20120062409A1
公开(公告)日：2012-03-15
申请号：US12879288
申请日：2010-09-10
申请人： Man-On Pun , Zafer Sahinoglu , Pu Wang
发明人： Man-On Pun , Zafer Sahinoglu , Pu Wang
IPC分类号： G01S13/04 , G01S13/00
CPC分类号： G01S7/292 , G01S13/04
摘要： A method detects a target in a radar signal using space-time adaptive processing. A test statistic is T = max α  max λ  ∫ R  f 1  ( x 0 , x 1 , …  , x K  α , λ , R )  p  ( R )   R max λ  ∫ R  f 0  ( x 0 , x 1 , …  , x K  λ , R )  p  ( R )   R , where x0 is a test signal, xk are K training signals, α is an unknown amplitude of a target signal within the test signal, λ is a scaling factor, R is a covariance matrix of the training signals, and a function max returns a maximum values. The test statistic is compared to a threshold to determine whether the target is present, or not.
摘要翻译：一种方法使用空时自适应处理来检测雷达信号中的目标。一个测试统计量是T = max（α，max，λ）∫R f f 1（x 0，x 1，...，x Kα，λ，R） R 0 f（x 0，x 1，...，x Kλ，R）p R（R）其中x0是测试信号，xk是K个训练信号，α是未知振幅的测试信号内的目标信号，λ是缩放因子，R是训练信号的协方差矩阵，函数max返回最大值。将测试统计量与阈值进行比较，以确定目标是否存在。

7. 发明授权

US08451956B2 SNR-based blanking scheme for impulsive noise mitigation in wireless networks 失效
标题翻译：用于无线网络中脉冲噪声抑制的基于SNR的消隐方案
公开(公告)号：US08451956B2
公开(公告)日：2013-05-28
申请号：US12650410
申请日：2009-12-30
申请人： Man-On Pun , Chunjie Duan , Zafer Sahinoglu , Dirk Brinkman
发明人： Man-On Pun , Chunjie Duan , Zafer Sahinoglu , Dirk Brinkman
IPC分类号： H04B1/10
CPC分类号： H04L25/067 , H04L1/0045 , H04L27/2647
摘要： A blanking scheme for mitigating impulsive noise in wireless networks is based on the signal-to-noise ratio (SNR) of symbols. To fully gain the benefits of the SNR-based blanking scheme, two methods are developed, namely a multi-level thresholding scheme in the time-, spatial- and frequency-domains, and a weighted-input error-correction decoding. The symbols are conditioned as a function of the estimated SNR in time-, frequency-, or spatial-domains or combinations therefore, and the conditioning is applied to an amplitude, phase, or energy level, or combinations thereof.
摘要翻译：用于减轻无线网络中的脉冲噪声的消隐方案是基于符号的信噪比（SNR）。为了充分获得基于SNR的消隐方案的优点，开发了两种方法，即时域，空间和频域中的多级阈值方案和加权输入纠错解码。符号在时间，频率或空间域或组合中作为估计的SNR的函数进行调节，并且将调节应用于幅度，相位或能级或其组合。

8. 发明授权

US08179300B2 Method for suppressing clutter in space-time adaptive processing systems 有权
标题翻译：用于抑制时空自适应处理系统中杂波的方法
公开(公告)号：US08179300B2
公开(公告)日：2012-05-15
申请号：US12696997
申请日：2010-01-29
申请人： Man-On Pun , Zafer Sahinoglu
发明人： Man-On Pun , Zafer Sahinoglu
IPC分类号： G01S13/00
CPC分类号： G01S13/00
摘要： A method surpresses clutter in a space-time adaptive processing system. The method achieves low-complexity computation via two steps. First, the method utilizes an improved fast approximated power iteration method to compress the data into a much smaller subspace. To further reduce the computational complexity, a progressive singular value decomposition (SVD) approach is employed to update the inverse of the covariance matrix of the compressed data. As a result, the proposed low-complexity STAP procedure can achieve near-optimal performance with order-of-magnitude computational complexity reduction as compared to the conventional STAP procedure.
摘要翻译：一种方法在时空自适应处理系统中抑制杂乱。该方法通过两个步骤实现低复杂度计算。首先，该方法利用改进的快速近似幂迭代方法将数据压缩成更小的子空间。为了进一步降低计算复杂度，采用渐进奇异值分解（SVD）方法来更新压缩数据的协方差矩阵的逆。结果，与传统的STAP过程相比，所提出的低复杂度STAP过程可以实现具有数量级的计算复杂度降低的接近最佳性能。

9. 发明申请

US20110187584A1 Method for Suppressing Clutter in Space-Time Adaptive Processing Systems 有权
标题翻译：在时空自适应处理系统中抑制杂波的方法
公开(公告)号：US20110187584A1
公开(公告)日：2011-08-04
申请号：US12696997
申请日：2010-01-29
申请人： Man-On Pun , Zafer Sahinoglu
发明人： Man-On Pun , Zafer Sahinoglu
IPC分类号： G01S13/00
CPC分类号： G01S13/00
摘要： A method surpresses clutter in a space-time adaptive processing system. The method achieves low-complexity computation via two steps. First, the method utilizes an improved fast approximated power iteration method to compress the data into a much smaller subspace. To further reduce the computational complexity, a progressive singular value decomposition (SVD) approach is employed to update the inverse of the covariance matrix of the compressed data. As a result, the proposed low-complexity STAP procedure can achieve near-optimal performance with order-of-magnitude computational complexity reduction as compared to the conventional STAP procedure.
摘要翻译：一种方法在时空自适应处理系统中抑制杂乱。该方法通过两个步骤实现低复杂度计算。首先，该方法利用改进的快速近似幂迭代方法将数据压缩成更小的子空间。为了进一步降低计算复杂度，采用渐进奇异值分解（SVD）方法来更新压缩数据的协方差矩阵的逆。结果，与传统的STAP过程相比，所提出的低复杂度STAP过程可以实现具有数量级的计算复杂度降低的接近最佳性能。

10. 发明申请

US20110158360A1 SNR-Based Blanking Scheme for Impulsive Noise Mitigation in Wireless Networks 失效
标题翻译：基于SNR的无线网络脉冲噪声消除消隐方案
公开(公告)号：US20110158360A1
公开(公告)日：2011-06-30
申请号：US12650410
申请日：2009-12-30
申请人： Man-On Pun , Chunjie Duan , Zafer Sahinoglu , Dirk Brinkman
发明人： Man-On Pun , Chunjie Duan , Zafer Sahinoglu , Dirk Brinkman
IPC分类号： H04B1/10
CPC分类号： H04L25/067 , H04L1/0045 , H04L27/2647
摘要： A blanking scheme for mitigating impulsive noise in wireless networks is based on the signal-to-noise ratio (SNR) of symbols. To fully gain the benefits of the SNR-based blanking scheme, two methods are developed, namely a multi-level thresholding scheme in the time-, spatial- and frequency-domains, and a weighted-input error-correction decoding. The symbols are conditioned as a function of the estimated SNR in time-, frequency-, or spatial-domains or combinations therefore, and the conditioning is applied to an amplitude, phase, or energy level, or combinations thereof.
摘要翻译：用于减轻无线网络中的脉冲噪声的消隐方案是基于符号的信噪比（SNR）。为了充分获得基于SNR的消隐方案的优点，开发了两种方法，即时域，空间和频域中的多级阈值方案和加权输入纠错解码。符号在时间，频率或空间域或组合中作为估计的SNR的函数进行调节，并且将调节应用于幅度，相位或能级或其组合。

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