An improved target tracking singer filter algorithm

Author

Hanguang Zhang ; Yan Chang ; Dai Liu ; Ke Ma

Author_Institution

Xi´an Electron. Eng. Res. Inst., Xi´an, China

fYear

2013

fDate

12-13 Oct. 2013

Firstpage

1070

Lastpage

1073

Abstract

Considering the low performance of accuracy and convergence of the traditional Singer algorithms for maneuvering detection, this paper proposed an improved Singer algorithm which deals with the adjustments of the matrix of the process noise covariance and changes of the filtering gain according to the average attenuation of innovation and the filtering value of acceleration. The new algorithm can reduce the RMSE of positions, and has the advantages of better filtering accuracy of velocity and acceleration. And the feasibility of the algorithm is proved by MATLAB simulations.

Keywords

convergence; covariance matrices; filtering theory; mean square error methods; target tracking; Matlab simulation; RMSE; acceleration filtering value; attenuation; convergence; detection maneuvering; filtering gain; process noise covariance matrix; root-mean-square error; target tracking Singer filter algorithm; Acceleration; Filtering; Mathematical model; Modeling; Noise; Target tracking; Technological innovation; average attenuation of innovation; maneuvering detection; process noise covariance; singer filtering algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on

Conference_Location

Dalian

Type

conf

DOI

10.1109/ICCSNT.2013.6967288

Filename

6967288