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Cramér-Rao Lower Bound for State-Constrained Nonlinear Filtering
2017 Edition, Volume 24, December 1, 2017 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

This letter presents a mean-square error lower bound for state estimation of nonlinear stochastic systems under given differentiable state constraints. Its recursive formulation permits incorporation of random process and measurement errors and is shown to...

Vector uniform Cramer-Rao lower bound
2004 Edition, September 1, 2004 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We develop a uniform Cramer-Rao lower bound (UCRLB) on the total variance of any estimator of an unknown deterministic vector of parameters, with bias gradient matrix whose norm is bounded by a constant. We consider two different measures of norm, leading to two...

Particle filtering and Cramer-Rao lower bound for underwater navigation
2003 Edition, Volume 6, January 1, 2003 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We have studied a sea navigation method relying on a digital underwater terrain map and sonar measurements. The method is applicable for both ships and underwater vessels. We have used experimental data to build an underwater map and to investigate the estimation performance. Since the...

A Cramer-Rao Lower Bound of CSI-based Indoor Localization
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Due to robustness against multi-path effect, frequency domain CSI (Channel State Information) of OFDM (Orthogonal Frequency Division Multiplexing) systems is supposed to provide good ranging measurement for indoor localization. Since lower bound of positioning error...

An Approximate Cramer-Rao Lower Bound for Multiple LFMCW Signals
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper we focus on deriving an approximate Cramer-Rao Lower Bound (CRLB) for the parameters of a multi-component Linear Frequency Modulated Continuous Wave (LFMCW) signal corrupted by complex additive white Gaussian noise. The approximation is necessary due...

A Cramer-Rao lower bound for complex parameters
1994 Edition, Volume 42, October 1, 1994 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

An expression is derived for a Cramer-Rao lower bound on the variance of unbiased estimators of complex parameters.< >

A CramerRao Lower Bound of CSI-Based Indoor Localization
2018 Edition, Volume 67, March 1, 2018 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Due to robustness against multipath effect, frequency domain CSI (Channel State Information) of OFDM (Orthogonal Frequency Division Multiplexing) systems is supposed to provide good ranging measurement for indoor localization. Since lower bound of positioning error...

The Hybrid Cramer-Rao Lower Bound - From Practice to Theory
2006 Edition, January 1, 2006 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In 1987, Rockah and Schultheiss (1987) introduced the hybrid Cramer-Rao lower bound (HCRLB ) as an extension of the classical Cramer-Rao bound (CRLB). Whereas the classical CRLB is applicable to the estimation of non-random parameters, and the...

Cramer-Rao lower bound for constrained complex parameters
2004 Edition, Volume 11, November 1, 2004 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

An expression for the Cramer-Rao lower bound (CRB) on the covariance of unbiased estimators of a constrained complex parameter vector is derived. The application and usefulness of the result is demonstrated through its use in the context of a semiblind...

Lognormal mixture Cramer-Rao lower bound for localization
2015 Edition, August 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In received signal strength (RSS) based localization problems, the accuracy of the position information obtained is closely associated with the RSS model used. Therefore, positioning success can be improved with a more accurate RSS model. In this study, to analyze the effect of RSS model in...

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