Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the ...Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.展开更多
Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rare...Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.展开更多
To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. ...To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).展开更多
By taking the subsequence out of the input-output sequence of a system polluted by white noise, an independent observation sequence and its probability density are obtained and then a maximum likelihood estimation of ...By taking the subsequence out of the input-output sequence of a system polluted by white noise, an independent observation sequence and its probability density are obtained and then a maximum likelihood estimation of the identification parameters is given. In order to decrease the asymptotic error, a corrector of maximum likelihood (CML) estimation with its recursive algorithm is given. It has been proved that the corrector has smaller asymptotic error than the least square methods. A simulation example shows that the corrector of maximum likelihood estimation is of higher approximating precision to the true parameters than the least square methods.展开更多
A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spect...A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spectral components that are assumed to follow the Gaussian probability density function(PDF). The proposed algorithm employs DBN learning in order to classify voice activity by using the input signal to calculate the likelihood ratio. Experiments show that the proposed algorithm yields improved results in various noise environments, compared to the conventional VAD algorithms. Furthermore, the DBN based algorithm decreases the detection probability of error with [0.7, 2.6] compared to the support vector machine based algorithm.展开更多
In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood ...In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood method are established. After that, the simulation data is identified to verify the correctness of the mathematic model and identification method. Last, the practical flight data is identified and analyzed.展开更多
Low elevation estimation,which has attracted wide attention due to the presence of specular multipath,is essential for tracking radars.Frequency agility not only has the advantage of strong anti-interference ability,b...Low elevation estimation,which has attracted wide attention due to the presence of specular multipath,is essential for tracking radars.Frequency agility not only has the advantage of strong anti-interference ability,but also can enhance the performance of tracking radars.A frequency-agile refined maximum likelihood(RML)algorithm based on optimal fusion is proposed.The algorithm constructs an optimization problem,which minimizes the mean square error(MSE)of angle estimation.Thereby,the optimal weight at different frequency points is obtained for fusing the angle estimation.Through theoretical analysis and simulation,the frequency-agile RML algorithm based on optimal fusion can improve the accuracy of angle estimation effectively.展开更多
The conformal array can make full use of the aperture,save space,meet the requirements of aerodynamics,and is sensitive to polarization information.It has broad application prospects in military,aerospace,and communic...The conformal array can make full use of the aperture,save space,meet the requirements of aerodynamics,and is sensitive to polarization information.It has broad application prospects in military,aerospace,and communication fields.The joint polarization and direction-of-arrival(DOA)estimation based on the conformal array and the theoretical analysis of its parameter estimation performance are the key factors to promote the engineering application of the conformal array.To solve these problems,this paper establishes the wave field signal model of the conformal array.Then,for the case of a single target,the cost function of the maximum likelihood(ML)estimator is rewritten with Rayleigh quotient from a problem of maximizing the ratio of quadratic forms into those of minimizing quadratic forms.On this basis,rapid parameter estimation is achieved with the idea of manifold separation technology(MST).Compared with the modified variable projection(MVP)algorithm,it reduces the computational complexity and improves the parameter estimation performance.Meanwhile,the MST is used to solve the partial derivative of the steering vector.Then,the theoretical performance of ML,the multiple signal classification(MUSIC)estimator and Cramer-Rao bound(CRB)based on the conformal array are derived respectively,which provides theoretical foundation for the engineering application of the conformal array.Finally,the simulation experiment verifies the effectiveness of the proposed method.展开更多
In this paper, an importance sampling maximum likelihood(ISML) estimator for direction-of-arrival(DOA) of incoherently distributed(ID) sources is proposed. Starting from the maximum likelihood estimation description o...In this paper, an importance sampling maximum likelihood(ISML) estimator for direction-of-arrival(DOA) of incoherently distributed(ID) sources is proposed. Starting from the maximum likelihood estimation description of the uniform linear array(ULA), a decoupled concentrated likelihood function(CLF) is presented. A new objective function based on CLF which can obtain a closed-form solution of global maximum is constructed according to Pincus theorem. To obtain the optimal value of the objective function which is a complex high-dimensional integral,we propose an importance sampling approach based on Monte Carlo random calculation. Next, an importance function is derived, which can simplify the problem of generating random vector from a high-dimensional probability density function(PDF) to generate random variable from a one-dimensional PDF. Compared with the existing maximum likelihood(ML) algorithms for DOA estimation of ID sources, the proposed algorithm does not require initial estimates, and its performance is closer to CramerRao lower bound(CRLB). The proposed algorithm performs better than the existing methods when the interval between sources to be estimated is small and in low signal to noise ratio(SNR)scenarios.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
随着风电渗透率的持续上升,电力系统的惯量水平显著下降,对系统频率稳定性构成了新的挑战。为有效评估风电并网情况下电力系统节点惯量的变化,提出了一种基于受控自回归滑动平均(autoregressive moving average with exogenous variable...随着风电渗透率的持续上升,电力系统的惯量水平显著下降,对系统频率稳定性构成了新的挑战。为有效评估风电并网情况下电力系统节点惯量的变化,提出了一种基于受控自回归滑动平均(autoregressive moving average with exogenous variable,ARMAX)模型的改进最大似然估计(maximum likelihood estimation,MLE)参数辨识方法对系统机组直接相连节点进行惯量评估。首先,构建ARMAX模型对发电机组直接相连节点的动态特性进行建模,并利用改进MLE对模型参数进行辨识,以评估与机组直接相连的节点惯量。然后,基于k-means聚类算法对发电机组节点惯量进行分区,计算得到系统区域惯量和中心频率,并进一步对非发电机组节点频率进行自适应多项式拟合计算,得到其系统节点惯量。最后,搭建IEEE39含风力发电机组节点系统,绘制热力图直观展示电力系统节点和区域的惯量分布,验证了所提改进方法的有效性。该方法有助于精准识别系统中不同节点的动态响应特性,为风电并网系统的分析和规划提供了有力支持。展开更多
【目的】设计一种基于FIML和DAE的填充缺失值的方法,即聚类全信息选择性过滤编码器数据填补算法(clustering-based comprehensive information selective filtering encoder data imputation algorithm,CFSM-DAE),为水稻种质资源缺失数...【目的】设计一种基于FIML和DAE的填充缺失值的方法,即聚类全信息选择性过滤编码器数据填补算法(clustering-based comprehensive information selective filtering encoder data imputation algorithm,CFSM-DAE),为水稻种质资源缺失数据进行填充。【方法】利用聚类辅助避免数据异常值对算法的影响,采用选择性过滤层用于识别高质量估算、减少低质量估算的影响。传统的DAE框架通常没有选择性过滤层,所有的估算值都被视为同等重要,无法区分高质量和低质量的估算值。为了进一步提高估算精度,研究采用集成框架将全信息最大似然性(FIML)与多对抗性自编码器(DAE)结合的方法(CFSM-DAE),在选择性过滤层基础上,自适应填充,即当估算值不符合设定阈值时,采用FIML填充策略以确保填充结果的稳定性和精确度,从而进一步来提高整体估算精度。在3种缺失数据机制(随机缺失(MAR)、完全随机缺失(MCAR)和非随机缺失(MNAR))下对模拟数据和实际水稻种质资源数据集进行研究,将CFSM-DAE方法与多种常用填充算法比较(全信息最大似然性(FIML)、对抗自编码器(DAE)、K近邻填充(KNN)、随机森林(RF)、链式方程多重插补(MICE))。【结果】CFSM-DAE在模拟数据上的表现为S_(RME)=0.0676,E_(MA)=0.0093,R^(2)=0.9958;在水稻种质资源数据上的表现为S_(RME)=0.0395,E_(MA)=0.0078,R^(2)=0.8913。相比之下,其他算法如DAE在这两类数据下的SRME表现分别为0.8896和0.7707;KNN算法的EMA表现分别为0.1183和0.1305;FIML算法的R2表现为0.3382和0.7321。因此,CFSM-DAE在多个评价指标上相较于其他算法都表现出了一定的提升,CFSM-DAE在模拟数据和水稻种质资源数据的表现优于其他算法。【结论】CFSM-DAE方法通过结合聚类、选择性过滤和全信息最大似然性等策略,显著提高了水稻种质资源数据中缺失值的填补精度,展示了其在处理复杂缺失值问题上的有效性和潜力。展开更多
因高度向分辨能力缺失,地基干涉雷达应用于建筑成像时会发生严重的高度向叠掩现象。层析合成孔径雷达(Tomographic Synthetic Aperture Radar,TomoSAR)技术具备高度向分辨能力,能够实现建筑三维成像。地基层析圆弧扫描合成孔径雷达(Grou...因高度向分辨能力缺失,地基干涉雷达应用于建筑成像时会发生严重的高度向叠掩现象。层析合成孔径雷达(Tomographic Synthetic Aperture Radar,TomoSAR)技术具备高度向分辨能力,能够实现建筑三维成像。地基层析圆弧扫描合成孔径雷达(Ground-based Tomographic Arc-scanning Synthetic Aperture Radar,GB-TomoArcSAR)通过双轴转台控制天线在不同俯仰角度的水平面内进行圆周扫描来获取高度向合成孔径,实现三维层析成像。本文提出了GB-TomoArcSAR的三维点云生成方法,首先构建了适用于高度向弧形采样条件的层析成像几何模型。其次利用基于巴特沃斯滤波器的奇异值分解(Singular Value Decomposition,SVD)方法进行谱估计,找出层析谱中的峰值及其对应的峰值位置,构成层析向目标候选集。随后利用自对消顺序广义似然比(Sequential Generalized Likelihood Ratio Test with Cancellation,SGLRTC)检测器估计散射体的数目与位置,通过设置检测门限将真实目标的峰值及对应的峰值位置从候选集中筛选出来。最后采用基于空间几何分布的点云优化方法剔除误差点,生成点云图像。文章通过点目标和面目标的仿真实验,验证了所提方法适用于GB-TomoArcSAR,能够有效解决高度向多散射体目标的叠掩问题;进一步开展了实测数据验证,基于所提方法获取了北京市一处建筑基坑的层析点云,其与实际场景几何特征一致。展开更多
基金Supported by the National Natural Science Foundation of China(12061017,12361055)the Research Fund of Guangxi Key Lab of Multi-source Information Mining&Security(22-A-01-01)。
文摘Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.
基金supported by the Fund for Foreign Scholars in University Research and Teaching Programs (B18039)。
文摘Beamspace super-resolution methods for elevation estimation in multipath environment has attracted significant attention, especially the beamspace maximum likelihood(BML)algorithm. However, the difference beam is rarely used in superresolution methods, especially in low elevation estimation. The target airspace information in the difference beam is different from the target airspace information in the sum beam. And the use of difference beams does not significantly increase the complexity of the system and algorithms. Thus, this paper applies the difference beam to the beamformer to improve the elevation estimation performance of BML algorithm. And the direction and number of beams can be adjusted according to the actual needs. The theoretical target elevation angle root means square error(RMSE) and the computational complexity of the proposed algorithms are analyzed. Finally, computer simulations and real data processing results demonstrate the effectiveness of the proposed algorithms.
基金supported by Joint Foundation of and China Academy of Engineering Physical (10676006)
文摘To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
文摘By taking the subsequence out of the input-output sequence of a system polluted by white noise, an independent observation sequence and its probability density are obtained and then a maximum likelihood estimation of the identification parameters is given. In order to decrease the asymptotic error, a corrector of maximum likelihood (CML) estimation with its recursive algorithm is given. It has been proved that the corrector has smaller asymptotic error than the least square methods. A simulation example shows that the corrector of maximum likelihood estimation is of higher approximating precision to the true parameters than the least square methods.
基金supported by the KERI Primary Research Program through the Korea Research Council for Industrial Science & Technology funded by the Ministry of Science,ICT and Future Planning (No.15-12-N0101-46)
文摘A novel technique is proposed to improve the performance of voice activity detection(VAD) by using deep belief networks(DBN) with a likelihood ratio(LR). The likelihood ratio is derived from the speech and noise spectral components that are assumed to follow the Gaussian probability density function(PDF). The proposed algorithm employs DBN learning in order to classify voice activity by using the input signal to calculate the likelihood ratio. Experiments show that the proposed algorithm yields improved results in various noise environments, compared to the conventional VAD algorithms. Furthermore, the DBN based algorithm decreases the detection probability of error with [0.7, 2.6] compared to the support vector machine based algorithm.
文摘In this paper a method of aerodynamic parameter identification of vehicle, the maximum likelihood method, is introduced. The aerodynamic model of vehicle is identified and the basic equations using maximum likelihood method are established. After that, the simulation data is identified to verify the correctness of the mathematic model and identification method. Last, the practical flight data is identified and analyzed.
基金supported by the Fund for Foreign Scholars in University Research and Teaching Programs(the 111 Project)(B18039).
文摘Low elevation estimation,which has attracted wide attention due to the presence of specular multipath,is essential for tracking radars.Frequency agility not only has the advantage of strong anti-interference ability,but also can enhance the performance of tracking radars.A frequency-agile refined maximum likelihood(RML)algorithm based on optimal fusion is proposed.The algorithm constructs an optimization problem,which minimizes the mean square error(MSE)of angle estimation.Thereby,the optimal weight at different frequency points is obtained for fusing the angle estimation.Through theoretical analysis and simulation,the frequency-agile RML algorithm based on optimal fusion can improve the accuracy of angle estimation effectively.
基金the National Natural Science Foundation of China(62071144,61971159,61871149).
文摘The conformal array can make full use of the aperture,save space,meet the requirements of aerodynamics,and is sensitive to polarization information.It has broad application prospects in military,aerospace,and communication fields.The joint polarization and direction-of-arrival(DOA)estimation based on the conformal array and the theoretical analysis of its parameter estimation performance are the key factors to promote the engineering application of the conformal array.To solve these problems,this paper establishes the wave field signal model of the conformal array.Then,for the case of a single target,the cost function of the maximum likelihood(ML)estimator is rewritten with Rayleigh quotient from a problem of maximizing the ratio of quadratic forms into those of minimizing quadratic forms.On this basis,rapid parameter estimation is achieved with the idea of manifold separation technology(MST).Compared with the modified variable projection(MVP)algorithm,it reduces the computational complexity and improves the parameter estimation performance.Meanwhile,the MST is used to solve the partial derivative of the steering vector.Then,the theoretical performance of ML,the multiple signal classification(MUSIC)estimator and Cramer-Rao bound(CRB)based on the conformal array are derived respectively,which provides theoretical foundation for the engineering application of the conformal array.Finally,the simulation experiment verifies the effectiveness of the proposed method.
基金supported by the basic research program of Natural Science in Shannxi province of China (2021JQ-369)。
文摘In this paper, an importance sampling maximum likelihood(ISML) estimator for direction-of-arrival(DOA) of incoherently distributed(ID) sources is proposed. Starting from the maximum likelihood estimation description of the uniform linear array(ULA), a decoupled concentrated likelihood function(CLF) is presented. A new objective function based on CLF which can obtain a closed-form solution of global maximum is constructed according to Pincus theorem. To obtain the optimal value of the objective function which is a complex high-dimensional integral,we propose an importance sampling approach based on Monte Carlo random calculation. Next, an importance function is derived, which can simplify the problem of generating random vector from a high-dimensional probability density function(PDF) to generate random variable from a one-dimensional PDF. Compared with the existing maximum likelihood(ML) algorithms for DOA estimation of ID sources, the proposed algorithm does not require initial estimates, and its performance is closer to CramerRao lower bound(CRLB). The proposed algorithm performs better than the existing methods when the interval between sources to be estimated is small and in low signal to noise ratio(SNR)scenarios.
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.
文摘随着风电渗透率的持续上升,电力系统的惯量水平显著下降,对系统频率稳定性构成了新的挑战。为有效评估风电并网情况下电力系统节点惯量的变化,提出了一种基于受控自回归滑动平均(autoregressive moving average with exogenous variable,ARMAX)模型的改进最大似然估计(maximum likelihood estimation,MLE)参数辨识方法对系统机组直接相连节点进行惯量评估。首先,构建ARMAX模型对发电机组直接相连节点的动态特性进行建模,并利用改进MLE对模型参数进行辨识,以评估与机组直接相连的节点惯量。然后,基于k-means聚类算法对发电机组节点惯量进行分区,计算得到系统区域惯量和中心频率,并进一步对非发电机组节点频率进行自适应多项式拟合计算,得到其系统节点惯量。最后,搭建IEEE39含风力发电机组节点系统,绘制热力图直观展示电力系统节点和区域的惯量分布,验证了所提改进方法的有效性。该方法有助于精准识别系统中不同节点的动态响应特性,为风电并网系统的分析和规划提供了有力支持。
文摘【目的】设计一种基于FIML和DAE的填充缺失值的方法,即聚类全信息选择性过滤编码器数据填补算法(clustering-based comprehensive information selective filtering encoder data imputation algorithm,CFSM-DAE),为水稻种质资源缺失数据进行填充。【方法】利用聚类辅助避免数据异常值对算法的影响,采用选择性过滤层用于识别高质量估算、减少低质量估算的影响。传统的DAE框架通常没有选择性过滤层,所有的估算值都被视为同等重要,无法区分高质量和低质量的估算值。为了进一步提高估算精度,研究采用集成框架将全信息最大似然性(FIML)与多对抗性自编码器(DAE)结合的方法(CFSM-DAE),在选择性过滤层基础上,自适应填充,即当估算值不符合设定阈值时,采用FIML填充策略以确保填充结果的稳定性和精确度,从而进一步来提高整体估算精度。在3种缺失数据机制(随机缺失(MAR)、完全随机缺失(MCAR)和非随机缺失(MNAR))下对模拟数据和实际水稻种质资源数据集进行研究,将CFSM-DAE方法与多种常用填充算法比较(全信息最大似然性(FIML)、对抗自编码器(DAE)、K近邻填充(KNN)、随机森林(RF)、链式方程多重插补(MICE))。【结果】CFSM-DAE在模拟数据上的表现为S_(RME)=0.0676,E_(MA)=0.0093,R^(2)=0.9958;在水稻种质资源数据上的表现为S_(RME)=0.0395,E_(MA)=0.0078,R^(2)=0.8913。相比之下,其他算法如DAE在这两类数据下的SRME表现分别为0.8896和0.7707;KNN算法的EMA表现分别为0.1183和0.1305;FIML算法的R2表现为0.3382和0.7321。因此,CFSM-DAE在多个评价指标上相较于其他算法都表现出了一定的提升,CFSM-DAE在模拟数据和水稻种质资源数据的表现优于其他算法。【结论】CFSM-DAE方法通过结合聚类、选择性过滤和全信息最大似然性等策略,显著提高了水稻种质资源数据中缺失值的填补精度,展示了其在处理复杂缺失值问题上的有效性和潜力。
文摘因高度向分辨能力缺失,地基干涉雷达应用于建筑成像时会发生严重的高度向叠掩现象。层析合成孔径雷达(Tomographic Synthetic Aperture Radar,TomoSAR)技术具备高度向分辨能力,能够实现建筑三维成像。地基层析圆弧扫描合成孔径雷达(Ground-based Tomographic Arc-scanning Synthetic Aperture Radar,GB-TomoArcSAR)通过双轴转台控制天线在不同俯仰角度的水平面内进行圆周扫描来获取高度向合成孔径,实现三维层析成像。本文提出了GB-TomoArcSAR的三维点云生成方法,首先构建了适用于高度向弧形采样条件的层析成像几何模型。其次利用基于巴特沃斯滤波器的奇异值分解(Singular Value Decomposition,SVD)方法进行谱估计,找出层析谱中的峰值及其对应的峰值位置,构成层析向目标候选集。随后利用自对消顺序广义似然比(Sequential Generalized Likelihood Ratio Test with Cancellation,SGLRTC)检测器估计散射体的数目与位置,通过设置检测门限将真实目标的峰值及对应的峰值位置从候选集中筛选出来。最后采用基于空间几何分布的点云优化方法剔除误差点,生成点云图像。文章通过点目标和面目标的仿真实验,验证了所提方法适用于GB-TomoArcSAR,能够有效解决高度向多散射体目标的叠掩问题;进一步开展了实测数据验证,基于所提方法获取了北京市一处建筑基坑的层析点云,其与实际场景几何特征一致。
