Sensors' optimal dimensionality compression matrix in estimation fusion

DOI10.1016/j.automatica.2005.07.011zbMath1100.93521OpenAlexW1982061042MaRDI QIDQ2576163

Jie Zhou, Enbin Song, Yunmin Zhu

Publication date: 8 December 2005

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2005.07.011

zbMATH Keywords

Linear compressionMinimum variance estimationMultisensor estimation fusion

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (5)

Distributed Kalman filtering fusion with packet loss or intermittent communications from local estimators to fusion center ⋮ Weighted measurement fusion quantized filtering with bandwidth constraints and missing measurements in sensor networks ⋮ Data reduction with quantization constraints for decentralized estimation in wireless sensor networks ⋮ Robust fusion filtering for multisensor time-varying uncertain systems: the finite horizon case ⋮ Nonlinear weighted measurement fusion unscented Kalman filter with asymptotic optimality

Cites Work

• Kalman filtering with real-time applications
• Optimal linear estimation fusion. I. Unified fusion rules
• On the track-to-track correlation problem
• Data fusion with minimal communication
• Optimal dimensionality reduction of sensor data in multisensor estimation fusion
• An Extremum Property of Sums of Eigenvalues
• Unnamed Item

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