Cramér–Rao Bounds for Filtering Based on Gaussian Process State-Space Models [Elektronisk resurs]

• Posterior Cramér-Rao bounds (CRBs) are derived for the estimation performance of three Gaussian process-based state-space models. The parametric CRB is derived for the case with a parametric state transition and a Gaussian process-based measurement model. We illustrate the theory with a target tracking example and derive both parametric and posterior filtering CRBs for this specific application. Finally, the theory is illustrated with a positioning problem, with experimental data from an office environment where the obtained estimation performance is compared to the derived CRBs. 

Ämnesord

Engineering and Technology  (hsv)

Electrical Engineering, Electronic Engineering, Information Engineering  (hsv)

Control Engineering  (hsv)

Teknik och teknologier  (hsv)

Elektroteknik och elektronik  (hsv)

Reglerteknik  (hsv)

Engineering and Technology  (hsv)

Electrical Engineering, Electronic Engineering, Information Engineering  (hsv)

Signal Processing  (hsv)

Teknik och teknologier  (hsv)

Elektroteknik och elektronik  (hsv)

Signalbehandling  (hsv)

Genre

government publication  (marcgt)

Indexterm och SAB-rubrik

Cramér-Rao bound; Gaussian process; statespace model; nonlinear estimation