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.File | Dimensione | Formato | |
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