We consider a cooperative filtering problem for a group of linear stochastic systems when both absolute linear measurements and relative nonlinear measurements are available. By extending the state of each system with the quadratic part we are able to derive a cooperative filter in the space of the quadratic recursively computable functions of the measurements. The exact value of the variance of the estimation error for each system can be explicitly computed.

Cooperative Filtering with Absolute and Relative Measurements / Battilotti, S.; Cacace, F.; D'Angelo, M.; Germani, A.. - (2018), pp. 7182-7187. (Intervento presentato al convegno 57th IEEE Conference on Decision and Control, CDC 2018 tenutosi a Miami; United States) [10.1109/CDC.2018.8619323].

Cooperative Filtering with Absolute and Relative Measurements

S. Battilotti;M. D'Angelo;
2018

Abstract

We consider a cooperative filtering problem for a group of linear stochastic systems when both absolute linear measurements and relative nonlinear measurements are available. By extending the state of each system with the quadratic part we are able to derive a cooperative filter in the space of the quadratic recursively computable functions of the measurements. The exact value of the variance of the estimation error for each system can be explicitly computed.
2018
57th IEEE Conference on Decision and Control, CDC 2018
copoperative filtering, measutements, kalman filters
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Cooperative Filtering with Absolute and Relative Measurements / Battilotti, S.; Cacace, F.; D'Angelo, M.; Germani, A.. - (2018), pp. 7182-7187. (Intervento presentato al convegno 57th IEEE Conference on Decision and Control, CDC 2018 tenutosi a Miami; United States) [10.1109/CDC.2018.8619323].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1185941
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