NDLI: Dynamic error spectrum for estimation performance evaluation: a case study on interacting multiple model algorithm

Content Provider	IET Digital Library
Author	Mao, Yanhui Han, Chongzhao Duan, Zhansheng
Abstract	The commonly used root-mean-square error for estimation performance evaluation is easily dominated by large error terms. So many new alternative absolute metrics have been provided in X. R. Li's work. However, each of these metrics only reflects one narrow aspect of estimation performance, respectively. A comprehensive measure, error spectrum, was presented aggregating all these incomprehensive measures. However, when being applied to dynamic systems, this measure will have three dimensions over the total time span, which is not intuitive and difficult to be analysed. To overcome its drawbacks, a new metric, dynamic error spectrum (DES), is proposed in this study to extend the error spectrum measure to dynamic systems. Three forms under different application backgrounds are given, one of which is balanced taking into account both good and bad behaviour of an estimator and so can provide more impartial evaluation results. It can be applied to a variety of dynamic systems directly. Then the challenge in performance evaluation of the interacting multiple model (IMM) algorithm is considered, and the IMM algorithm is chosen as the testing case to illustrate the superiority of the DES metric. The simulation results validate its utility and effectiveness.
Starting Page	202
Ending Page	210
Page Count	9
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 2, Apr (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0134
Journal	IET Signal Processing
Publisher Date	2013-09-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	DES Metric Dynamic Error Spectrum Dynamic System Estimation Performance Estimation Theory IMM Algorithm Interacting Multiple Model Algorithm Interpolation And Function Approximation Mean Square Error Method Multiple Model Algorithm Numerical Analysis Numerical Approximation And Analysis Performance Evaluation Probability Theory Root Mean Square Error Statistics Stochastic Linearised SCUC
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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