A novel multi-baseline phase unwrapping algorithm based on the unscented particle filter for interferometric synthetic aperture radar （INSAR） technology application is proposed. The proposed method is not constraine...A novel multi-baseline phase unwrapping algorithm based on the unscented particle filter for interferometric synthetic aperture radar （INSAR） technology application is proposed. The proposed method is not constrained by the nonlinearity of the problem and is independent of noise statistics, and performs noise eliminating and phase unwrapping at the same time by combining with an unscented particle filter with a path-following strategy and an omni-directional local phase slope estimator. Results obtained from multi-baseline synthetic data and single-baseline real data show the performance of the proposed method.展开更多
WRAP(Water Rights Analysis Package)水权分析模型是基于水资源优先分配制度来模拟和预测一个或多个流域内水资源使用及管理的模型。作者首次将WRAP水权分析模型应用于北京通州区,以1956～2007年通州区相关资料作为模型的计算数据,模...WRAP(Water Rights Analysis Package)水权分析模型是基于水资源优先分配制度来模拟和预测一个或多个流域内水资源使用及管理的模型。作者首次将WRAP水权分析模型应用于北京通州区,以1956～2007年通州区相关资料作为模型的计算数据,模拟与计算结果表明:通州地区的天然年径流总体趋势基本保持不变,调度径流呈微弱增长趋势,两者的年际变差均逐渐剧烈;历年的径流消耗量总体趋势亦基本不变,但回归流呈逐渐增长趋势;研究区内多年平均水量保证率为59.9%,工业用水、城镇生活用水和农村生活用水呈上升趋势,而农业用水量总体呈下降趋势。展开更多
A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for represent...A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.展开更多
This paper takes further insight into the sparse geometry which offers a larger array aperture than uniform linear array(ULA)with the same number of physical sensors.An efficient method based on closed-form robust Chi...This paper takes further insight into the sparse geometry which offers a larger array aperture than uniform linear array(ULA)with the same number of physical sensors.An efficient method based on closed-form robust Chinese remainder theorem(CFRCRT)is presented to estimate the direction of arrival(DOA)from their wrapped phase with permissible errors.The proposed algorithm has significantly less computational complexity than the searching method while maintaining similar estimation precision.Furthermore,we combine all phase discrete Fourier transfer(APDFT)and the CFRCRT algorithm to achieve a considerably high DOA estimation precision.Both the theoretical analysis and simulation results demonstrate that the proposed algorithm has a higher estimation precision as well as lower computation complexity.展开更多
基金supported by the National Natural Science Foundation of China(41201479)the Scientific Research Project of Guilin University of Electronic Technology(UF11015Y)
文摘A novel multi-baseline phase unwrapping algorithm based on the unscented particle filter for interferometric synthetic aperture radar （INSAR） technology application is proposed. The proposed method is not constrained by the nonlinearity of the problem and is independent of noise statistics, and performs noise eliminating and phase unwrapping at the same time by combining with an unscented particle filter with a path-following strategy and an omni-directional local phase slope estimator. Results obtained from multi-baseline synthetic data and single-baseline real data show the performance of the proposed method.
文摘WRAP(Water Rights Analysis Package)水权分析模型是基于水资源优先分配制度来模拟和预测一个或多个流域内水资源使用及管理的模型。作者首次将WRAP水权分析模型应用于北京通州区,以1956～2007年通州区相关资料作为模型的计算数据,模拟与计算结果表明:通州地区的天然年径流总体趋势基本保持不变,调度径流呈微弱增长趋势,两者的年际变差均逐渐剧烈;历年的径流消耗量总体趋势亦基本不变,但回归流呈逐渐增长趋势;研究区内多年平均水量保证率为59.9%,工业用水、城镇生活用水和农村生活用水呈上升趋势,而农业用水量总体呈下降趋势。
基金Project(50808025) supported by the National Natural Science Foundation of ChinaProject(20090162110057) supported by the Doctoral Fund of Ministry of Education,China
文摘A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.
基金supported by the Fund for Foreign Scholars in University Research and Teaching Programs(the 111 Project)(B18039)
文摘This paper takes further insight into the sparse geometry which offers a larger array aperture than uniform linear array(ULA)with the same number of physical sensors.An efficient method based on closed-form robust Chinese remainder theorem(CFRCRT)is presented to estimate the direction of arrival(DOA)from their wrapped phase with permissible errors.The proposed algorithm has significantly less computational complexity than the searching method while maintaining similar estimation precision.Furthermore,we combine all phase discrete Fourier transfer(APDFT)and the CFRCRT algorithm to achieve a considerably high DOA estimation precision.Both the theoretical analysis and simulation results demonstrate that the proposed algorithm has a higher estimation precision as well as lower computation complexity.
