| 1. |
- Akcay, H., et al.
(författare)
-
On the choice of norms in system identification
- 1996
-
Ingår i: IEEE Transactions on Automatic Control. - Linköping : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286. ; 41:9, s. 1367-1372
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C > 0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all ℓp-norms, p ≀ 2 < ∞ for F(C). ©1996 IEEE.
|
|
| 2. |
- Andersson, Magnus, et al.
(författare)
-
Avoiding Mode Pairing when Updating Finite Element Models
- 1997
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Updating nite element models of complex mechanical structures requires some extra considerations. It is stressed that the two most important aspects on updating finite element models are parameter estimation properties and computational expenses. A novel mode-pairing free model updating formulation is found to hav egood parameter estimation properties. The computational expenses are reduced with a semi-fixed modal basis, kept fixed during several iterations.
|
|
| 3. |
- Andersson, Magnus
(författare)
-
Noise Robust Actuator Placement on Flexible Structures
- 1997
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A novel criterion for placement of actuators on flexible mechanical structures is presented. Using simulated "measured modes" obtained from the model, the proposed criterion maximizes the correlation of the measured modes and the normal modes. The measured modes deviate from the normal modes due to damping, measurement noise and process noise. The statistical properties of the criterion are investigated. In simulations the computed actuator locations on a small aircraft-like model shows increased robustness properties against damping, for an acceptable loss of correlation. A computationally cheap actuator placement algorithm is proposed.
|
|
| 4. |
- Andersson, Mats, et al.
(författare)
-
Sequential Filter Trees for Efficient 2D 3D and 4D Orientation Estimation
- 1998
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A recursive method to condense general multidimensional FIR-filters into a sequence of simple kernels with mainly one dimensional extent has been worked out. Convolver networks adopted for 2, 3 and 4D signals is presented and the performance is illustrated for spherically separable quadrature filters. The resulting filter responses are mapped to a non biased tensor representation where the local tensor constitutes a robust estimate of both the shape and the orientation (velocity) of the neighbourhood. A qualitative evaluation of this General Sequential Filter concept results in no detectable loss in accuracy when compared to conventional FIR (Finite Impulse Response) filters but the computational complexity is reduced several orders in magnitude. For the examples presented in this paper the attained speed-up is 5, 25 and 300 times for 2D, 3D and 4D data respectively The magnitude of the attained speed-up implies that complex spatio-temporal analysis can be performed using standard hardware, such as a powerful workstation, in close to real time. Due to the soft implementation of the convolver and the tree structure of the sequential filtering approach the processing is simple to reconfigure for the outer as well as the inner (vector length) dimensionality of the signal. The implementation was made in AVS (Application Visualization System) using modules written in C.
|
|
| 5. |
- Bergman, Niclas
(författare)
-
A Bayesian Approach to Terrain-Aided Navigation
- 1996
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The terrain-aided navigation problem is a highly nonlinear estimation problem with application to aircraft navigation and missile guidance. In this work the Bayesian approach is used to estimate the aircraft position. With a quantization of the state space an implementable algorithm is found. Problems with low excitation, rough terrain and parallel position hypothesis are handled in a reliable way. The algorithm is evaluated using simulations on real terrain databases.
|
|
| 6. |
- Bergman, Niclas
(författare)
-
A Bayesian Approach to Terrain-Aided Navigation II
- 1997
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The terrain-aided navigation problem is a highly nonlinear estimation problem with application to aircraft navigation and missile guidance. In this work the Bayesian approach is used to estimate the aircraft position. With a quantization of the state space an implementable algorithm is found. Problems with low excitation, rough terrain and parallel position hypothesis are handled in a reliable way. The algorithm is evaluated using simulations on real terrain databases.
|
|
| 7. |
- Bergman, Niclas
(författare)
-
Deterministic and Stochastic Bayesian Methods in Terrain Navigation
- 1998
-
Ingår i: Proceedings of the 37th IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780343948 ; , s. 227-232 vol.1
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Terrain navigation is an application where inference between conceptually different sensors is performed recursively online. In this work the Bayesian framework of statistical inference is applied to this recursive estimation problem. Three algorithms for approximative Bayesian estimation are evaluated in simulations, one deterministic algorithm and two stochastic. The deterministic method solve the Bayesian inference problem by numerical integration while the stochastic methods simulate several candidate solutions and evaluates the integral by averaging between these candidates. Simulations show that all three algorithms are efficient and approximately reach the Cramer-Rao bound. However, the stochastic methods are sensitive to outliers and the deterministic method has the limitation of being hard to implement in higher dimensions.
|
|
| 8. |
- Bergman, Niclas
(författare)
-
Expectation Maximization Segmentation
- 1998
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report reviews the Expectation Maximization EM algorithm and applies it to the data segmentation problem yielding the Expectation Maximization Segmentation EMS algorithm The EMS algorithm requires batch processing of the data and can be applied to mode switching or jumping linear dynamical state space models The EMS algorithm consists of an optimal fusion of fixed interval Kalman smoothing and discrete optimization.The next section gives a short introduction to the EM algorithm with some background and convergence results In Section the data segmentation problem is dened and in Section the EM algorithm is applied to this problem Section contains simulation results and Section some conclusive remarks.
|
|
| 9. |
|
|
| 10. |
- Bergman, Niclas, et al.
(författare)
-
Terrain Navigation using Bayesian Statistics
- 1999
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In aircraft navigation the demands on reliability and safety are very high. The importance of accurate position and velocity information becomes crucial when flying an aircraft at low altitudes, and especially during the landing phase. Not only should the navigation system have a consistent description of the position of the aircraft, but also a description of the surrounding terrain, buildings and other objects that are close to the aircraft. Terrain navigation is a navigation scheme that utilizes variations in the terrain height along the aircraft flight path. Integrated with an Inertial Navigation System (INS), it yields high performance position estimates in an autonomous manner, ie without any support information sent to the aircraft. In order to obtain these position estimates, a nonlinear recursive estimation problem must be solved on-line. Traditionally, this filtering problem has been solved by local linearization of the terrain at one or several assumed aircraft positions. Due to changing terrain characteristics, these linearizations will in some cases result in diverging position estimates. In this work, we show how the Bayesian approach gives a comprehensive framework for solving the recursive estimation problem in terrain navigation. Instead of approximating the model of the estimation problem, the analytical solution is approximately implemented. The proposed navigation filter computes a probability mass distribution of the aircraft position and updates this description recursively with each new measurement. The navigation filter is evaluated over a commercial terrain database, yielding accurate position estimates over several types of terrain characteristics. Moreover, in a Monte Carlo analysis, it shows optimal performance as it reaches the Cramér-Rao lower bound.
|
|
