To estimate the motion parameters of a moving target before its passing by the closest point of approach （CPA） point in a low frequency analyzing and recording （LOFAR） field, an error-free theoretical method based...To estimate the motion parameters of a moving target before its passing by the closest point of approach （CPA） point in a low frequency analyzing and recording （LOFAR） field, an error-free theoretical method based on the joint measurement of target radiated noise＇s amplitude and frequency was presented. First, the error-free theoretical equations for target characteristic frequency, absolute velocity, the CPA, and amplitude of the radiation noise were derived by three equal interval measured values of the target amplitude and frequency. Then, the method to improve the calculation accuracy was given. Finally, the simulation and experiments were conducted in the air and showed the correctness of this method. By using one single piece of LOFAR, this method can calculate four target parameters and the relative error of each estimated parameter is less than 10%.展开更多
In this paper we study the proximal point algorithm (PPA) based predictioncorrection (PC) methods for monotone variational inequalities. Each iteration of these methods consists of a prediction and a correction. The p...In this paper we study the proximal point algorithm (PPA) based predictioncorrection (PC) methods for monotone variational inequalities. Each iteration of these methods consists of a prediction and a correction. The predictors are produced by inexact PPA steps. The new iterates are then updated by a correction using the PPA formula. We present two profit functions which serve two purposes: First we show that the profit functions are tight lower bounds of the improvements obtained in each iteration. Based on this conclusion we obtain the convergence inexactness restrictions for the prediction step. Second we show that the profit functions are quadratically dependent upon the step lengths, thus the optimal step lengths are obtained in the correction step. In the last part of the paper we compare the strengths of different methods based on their inexactness restrictions.展开更多
基金Project supported by the National Natural Science Foundation of China （No. 51209173）
文摘To estimate the motion parameters of a moving target before its passing by the closest point of approach （CPA） point in a low frequency analyzing and recording （LOFAR） field, an error-free theoretical method based on the joint measurement of target radiated noise＇s amplitude and frequency was presented. First, the error-free theoretical equations for target characteristic frequency, absolute velocity, the CPA, and amplitude of the radiation noise were derived by three equal interval measured values of the target amplitude and frequency. Then, the method to improve the calculation accuracy was given. Finally, the simulation and experiments were conducted in the air and showed the correctness of this method. By using one single piece of LOFAR, this method can calculate four target parameters and the relative error of each estimated parameter is less than 10%.
基金The author was supported by NSFC Grant 10271054MOEC grant 20020284027 and Jiangsur NSF grant BK20002075.
文摘In this paper we study the proximal point algorithm (PPA) based predictioncorrection (PC) methods for monotone variational inequalities. Each iteration of these methods consists of a prediction and a correction. The predictors are produced by inexact PPA steps. The new iterates are then updated by a correction using the PPA formula. We present two profit functions which serve two purposes: First we show that the profit functions are tight lower bounds of the improvements obtained in each iteration. Based on this conclusion we obtain the convergence inexactness restrictions for the prediction step. Second we show that the profit functions are quadratically dependent upon the step lengths, thus the optimal step lengths are obtained in the correction step. In the last part of the paper we compare the strengths of different methods based on their inexactness restrictions.
