Error Model-converted Measurement and Error Model-modified Extended Kalman Filters for Target Tracking | Zendy

Sudesh K. Kashyap | Zendy; G Girija | Zendy; Jitendra R. Raol | Zendy

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Error Model-converted Measurement and Error Model-modified Extended Kalman Filters for Target Tracking

Author(s) -

Sudesh K. Kashyap,

G Girija,

Jitendra R. Raol

Publication year - 2006

Publication title -

defence science journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.198

H-Index - 32

eISSN - 0976-464X

pISSN - 0011-748X

DOI - 10.14429/dsj.56.1932

Subject(s) - kalman filter , tracking (education) , control theory (sociology) , tracking error , computer science , extended kalman filter , moving horizon estimation , fast kalman filter , errors in variables models , artificial intelligence , machine learning , psychology , pedagogy , control (management)

Two-filter schemes have been evaluated to handle the polar measurements using error model (for bias correction and measurement noise covariance computation)for target-tracking application. It is assumed that a good reference source of target information is available. Schemes based on error model converted measurement Kalman filter (ECMKF) and error model modified extended-Kalman filter (EMEKF) algorithms are presented. Also some comparison with CMKF(debiased) is given. It is inferred that EMEKF gives better performance compared to other filters. Features of EMEKF is carried out wrt to processing order of radar measurement channels.

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