Multi-Sensor Fusion Adaptive Estimation for Nonlinear Under-observed System with Multiplicative Noise

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外文摘要：The adaptive fusion estimation problem was studied for the multi-sensor nonlinear under-observed systems with multiplicative noise.A one-step predictor with state update equations was designed for the virtual state with virtual noise first of all.An extended incremental Kalman filter(EIKF)was then proposed for the nonlinear un-der-observed systems.Furthermore,an adaptive filtering method was given for optimization.The fusion adaptive in-cremental Kalman filter weighted by scalar was finally proposed.The comparison analysis was made to verify the op-timization of the state estimation using adaptive filtering method in the filtering process.

外文关键词：

Information fusionMultiplicative noiseUnder-observed systemsAdaptive filteringIncremental filtering

作者：

Yongpeng CUI、Xiaojun SUN

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作者单位：

School of Electronic Engineering,Heilongjiang University,Harbin 150080,China

Key Laboratory of Information Fusion Estimation and Detection,Harbin 150080,China

基金：

National Natural Science Foundation of ChinaSpecial Fund Project for Basic Scientific Research Business Expenses of Colleges and Universities in Heilongjiang Province

项目编号：

611042092020-KYYWF-0098

出版年：

2024

DOI：

10.23919/cje.2022.00.364

电子学报(英文)

CSTPCDEI

ISSN：1022-4653

年,卷(期)：2024.33(1)

参考文献量33