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Target tracking methods based on a signal-to-noise ratio model 被引量:2
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作者 Dai liU Yong-bo ZHAO +2 位作者 Zi-qiao YUAN jie-tao li Guo-ji CHEN 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2020年第12期1804-1814,共11页
In traditional target tracking methods,the angle error and range error are often measured by the empirical value,while observation noise is a constant.In this paper,the angle error and range error are analyzed.They ar... In traditional target tracking methods,the angle error and range error are often measured by the empirical value,while observation noise is a constant.In this paper,the angle error and range error are analyzed.They are influenced by the signalto-noise ratio(SNR).Therefore,a model related to SNR has been established,in which the SNR information is applied for target tracking.Combined with an advanced nonlinear filter method,the extended Kalman filter method based on the SNR model(SNR-EKF)and the unscented Kalman filter method based on the SNR model(SNR-UKF)are proposed.There is little difference between the SNR-EKF and SNR-UKF methods in position precision,but the SNR-EKF method has advantages in computation time and the SNR-UKF method has advantages in velocity precision.Simulation results show that target tracking methods based on the SNR model can greatly improve the tracking performance compared with traditional tracking methods.The target tracking accuracy and convergence speed of the proposed methods have significant improvements. 展开更多
关键词 Signal-to-noise ratio(SNR)model Target tracking Angle error Range error Nonlinear filter
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