loading
An intrinsic Cramér-Rao bound on SO(3) for (dynamic) attitude filtering
2015 Edition, December 1, 2015 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this note an intrinsic version of the Cramér-Rao bound on estimation accuracy is established on the Special Orthogonal group SO(3). It is intrinsic in the sense that it does not rely on a specific choice of coordinates...

Application of nonlinear Kalman filter approach in dynamic GPS-based attitude determination
1997 Edition, Volume 2, January 1, 1997 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this paper, nonlinear Kalman filter technique is applied to dynamic GPS-based attitude determination. The governing equation that characterizes the attitude information and GPS measurements is developed. A nonlinear Kalman filter algorithm is then formulated to...

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...

Concentrated Cramer-Rao bound expressions
1994 Edition, Volume 40, March 1, 1994 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We present a method to simplify the analytical computation of the Cramer-Rao bound. The method circumvents bound calculations for so-called nuisance parameters. Under mild regularity conditions the technique, which replaces expectations with almost sure...

A modified attitude algorithm for the adaptive Kalman filter in high dynamic environment
2017 Edition, October 1, 2017 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

The attitude and heading reference system adopted by loitering vehicle is unable to maintain a stable measurement precision during long maneuvering of the carrier due to large errors. For this problem, an adaptive filtering algorithm that provides adaptive adjustment of...

Improvements on the Cramer-Rao bound
1991 Edition, January 1, 1991 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In the context of nonrandom parameter estimation from a finite set of observations, the situation associated with weak Cramer-Rao bounds is addressed. It is shown that it is possible to improve the Cramer-Rao bound by incorporating higher-order derivatives of the...

Cramér-Rao Lower Bound on AoA Estimation Using an RF Lens-embedded Antenna Array
Volume PP - IEEE - Institute of Electrical and Electronics Engineers, Inc.

In this letter, we investigate the Cramer-Rao lower bound (CRLB) on angle of arrival (AoA) estimation of an RF lens-embedded antenna array. We first derive an expression for the received signal, in terms of intrinsic lens characteristics,...

Intrinsic Cramer-Rao bounds and subspace estimation accuracy
2000 Edition, January 1, 2000 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

Signal processing estimation problems are traditionally posed for a set of given, if unknown, parameters, such as angle and/or Doppler. Nevertheless, there are estimation problems on manifolds where no set of intrinsic coordinates exist. One example encountered frequently is...

An adaptive kalman filter for three dimensional attitude tracking
2011 Edition, March 1, 2011 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

An adaptive kalman filter for three dimensional attitude tracking is presented in this paper. Such filter can be used in the low cost system with only a triaxis accelerometer and a triaxis magnetometer where dynamic attitude tracking is needed....

Misspecified Bayesian Cramér-Rao Bound for Sparse Bayesian
2018 Edition, June 1, 2018 - IEEE - Institute of Electrical and Electronics Engineers, Inc.

We consider a misspecified Bayesian Cramér-Raobound (MBCRB), justified in a scenario where the assumed data model is different from the true generative model. As an example of this scenario, we study a popular sparse Bayesian learning (SBL) algorithm where the assumed data model,...

Advertisement