研究了两部2D雷达组网中的目标定位估计和定位精度问题。为考虑地球曲率对目标定位精度的影响,提出了两雷达站组网中基于实际地球椭球模型的几何交叉定位与数据融合相结合的方法,建立了两部雷达观测定位几何模型,推导了定位方程和精度...研究了两部2D雷达组网中的目标定位估计和定位精度问题。为考虑地球曲率对目标定位精度的影响,提出了两雷达站组网中基于实际地球椭球模型的几何交叉定位与数据融合相结合的方法,建立了两部雷达观测定位几何模型,推导了定位方程和精度估计公式并进行了误差分析。仿真分析表明,在选择更为实际的观测模型的前提下,利用几何定位与数据融合方法不但改善了两雷达的定位性能,而且根据定位几何精度因子(geometricaldilution of precision,GDOP)图的特点,选择相应的定位雷达,提高了雷达站组合的几何定位精度。展开更多
In order to enhance the location estimation performance of mobile station（MS）tracking and positioning, a new method of mobile location optimal estimation based on the federated filtering structure and the simplified...In order to enhance the location estimation performance of mobile station（MS）tracking and positioning, a new method of mobile location optimal estimation based on the federated filtering structure and the simplified unscented Kalman filter （UKF） is presented. The proposed algorithm uses the Singer mobile statement model as the reference system, and the simplified UKF as the subfilters. The subfilters receive the two groups of independently detected time difference of arrival （TDOA） measurement inputs and Doppler measurement inputs, and produce local estimation outputs to the main estimator. Then the main estimator performs the optimal fusion of the local estimation outputs according to the scalar weighted rule, and a global optimal or suboptimal estimation result is achieved. Finally the main estimator gives feedback and reset information to the subfilters and the reference system for next step estimation. In the simulations, the estimation performance of the proposed algorithm is evaluated and compared with the simplified UKF method with TDOA or Doppler measurement alone. The simulation results demonstrate that the proposed algorithm can effectively reduce the location estimation error and variance of the MS, and has favorable performance in both root mean square error（RMSE） and mean error cumulative distribution function（CDF）.展开更多
This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its ana...This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its analysis. Three kinds of indicators, both specific and general, are applied in both methods. Thorough consideration is given to short-term international capital inflow from trade, other current account items, capital account, and errors and omissions, as well as other channels through which short term capital might accrue to a nation＇s balance. Based on a comprehensive comparison of year-on-year data, this paper also estimates monthly data using a simplified, indirect calculation approach. Estimates show that, despite a degree of difference in results between methods, most estimates are highly consistent for a given period. Based on monthly estimates, we conclude that turbulence in international financial markets （i.e., the United States subprime mortgage crisis and the European sovereign debt crisis） has had a major impact on China ＇s short-term capital flow.展开更多
This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local...This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.展开更多
文摘研究了两部2D雷达组网中的目标定位估计和定位精度问题。为考虑地球曲率对目标定位精度的影响,提出了两雷达站组网中基于实际地球椭球模型的几何交叉定位与数据融合相结合的方法,建立了两部雷达观测定位几何模型,推导了定位方程和精度估计公式并进行了误差分析。仿真分析表明,在选择更为实际的观测模型的前提下,利用几何定位与数据融合方法不但改善了两雷达的定位性能,而且根据定位几何精度因子(geometricaldilution of precision,GDOP)图的特点,选择相应的定位雷达,提高了雷达站组合的几何定位精度。
基金The Cultivation Fund of the Key Scientific and Technical Innovation Project of Ministry of Education of China(No.706028)
文摘In order to enhance the location estimation performance of mobile station（MS）tracking and positioning, a new method of mobile location optimal estimation based on the federated filtering structure and the simplified unscented Kalman filter （UKF） is presented. The proposed algorithm uses the Singer mobile statement model as the reference system, and the simplified UKF as the subfilters. The subfilters receive the two groups of independently detected time difference of arrival （TDOA） measurement inputs and Doppler measurement inputs, and produce local estimation outputs to the main estimator. Then the main estimator performs the optimal fusion of the local estimation outputs according to the scalar weighted rule, and a global optimal or suboptimal estimation result is achieved. Finally the main estimator gives feedback and reset information to the subfilters and the reference system for next step estimation. In the simulations, the estimation performance of the proposed algorithm is evaluated and compared with the simplified UKF method with TDOA or Doppler measurement alone. The simulation results demonstrate that the proposed algorithm can effectively reduce the location estimation error and variance of the MS, and has favorable performance in both root mean square error（RMSE） and mean error cumulative distribution function（CDF）.
文摘This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its analysis. Three kinds of indicators, both specific and general, are applied in both methods. Thorough consideration is given to short-term international capital inflow from trade, other current account items, capital account, and errors and omissions, as well as other channels through which short term capital might accrue to a nation＇s balance. Based on a comprehensive comparison of year-on-year data, this paper also estimates monthly data using a simplified, indirect calculation approach. Estimates show that, despite a degree of difference in results between methods, most estimates are highly consistent for a given period. Based on monthly estimates, we conclude that turbulence in international financial markets （i.e., the United States subprime mortgage crisis and the European sovereign debt crisis） has had a major impact on China ＇s short-term capital flow.
基金supported by the National Natural Science Foundation of China under Grant Nos.60934009, 60901037 and 61004138
文摘This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.
