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Posterior Cramér-Rao bound and suboptimal filtering for IMU/GNSS based cooperative train localization
2016 Edition, April 1, 2016 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

The optimal estimator for the hidden state of nonlinear systems is often not known or it is computational unfeasible. In this situation suboptimal algorithms must be used. An important performance metric for these algorithms is the difference...

Posterior Cramér-Rao bounds for discrete-time nonlinear filtering with finitely correlated noises
2015 Edition, July 1, 2015 - Technical Committee on Control Theory, Chinese Association of Automation

In this paper, a recursive formula of the mean-square error lower bound for the discrete-time nonlinear filtering problem when noises of dynamic systems are temporally correlated is derived based on the Van Trees (posterior) version of...

Nonlinear event-based state estimation using sequential Monte Carlo approach
2017 Edition, December 1, 2017 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

State estimation of nonlinear stochastic system in the setting of event-based (EB) measurements is quite challenging, because the measurements are not available at each sampling period, but are available only when a certain pre-specified event occurs. Recently, a...

Posterior Cramer-Rao bounds for discrete-time nonlinear filtering
1998 Edition, Volume 46, May 1, 1998 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

A mean-square error lower bound for the discrete-time nonlinear filtering problem is derived based on the van Trees (1968) (posterior) version of the Cramer-Rao inequality. This lower bound is applicable to...

Conditional Posterior Cramér-Rao lower bounds for nonlinear recursive filtering
2009 Edition, July 1, 2009 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Posterior Cramér Rao lower bounds (PCRLBs) [1] for sequential Bayesian estimators provide performance bounds for general nonlinear filtering problems and have been used widely for sensor management in tracking and fusion systems. However, the...

High-Order Analysis of the Efficiency Gap for Maximum Likelihood Estimation in Nonlinear Gaussian Models
2018 Edition, Volume 66, September 15, 2018 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In Gaussian measurement models, the measurements are given by a known function of the unknown parameter vector, contaminated by additive zero-mean Gaussian noise. When the function is linear, the resulting maximum likelihood estimate (MLE) is well-known to be efficient...

A radar application of a modified Cramer-Rao bound: parameter estimation in non-Gaussian clutter
1998 Edition, Volume 46, July 1, 1998 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper, we derive a lower bound on the error covariance matrix for any unbiased estimator of the parameters of a signal composed of a mixture of spherically invariant random processes (SIRPs). The proposed approach represents a special case of...

Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation
2016 Edition, July 1, 2016 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the...

Multi-user CFOs Estimation for SC-FDMA System Over Frequency Selective Fading Channels
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Frequency synchronization in single-carrier frequency division multiple access (SC-FDMA) uplink system is a challenging task due to the presence of different carrier frequency offsets (CFOs) for different users. In this paper, we propose a blind CFOs estimation algorithm...

State estimation of nonlinear systems with Markov state reset
2008 Edition, December 1, 2008 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We present a novel observer design for a class of single-output nonlinear systems with Markov jumps. The Markov jump process interferes with a deterministic nonlinear dynamics at random times and retains its state for a certain amount of time (dwell...

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