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The global information vector and information matrix (left (widehat {mathbf {y}}_{k|k}, mathbf {Y}_{k|k}right)) are obtained by fusing the received surprisal information contributions and its own information contributions (i f,k,I f,k ) with the predicted information vector and matrix (left (widehat {mathbf {y}}_{k|k-1}, mathbf {Y}_{k|k-1}right)).
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Thus, the FC can fuse the arriving information contribution in time.
Hence, they can calculate the local information metrics (information contribution vector and matrix) based on their observations.
Hence, each camera c i where i∈C k that observes the object computes its own information contribution vector i i,k and information contribution matrix I i,k as shown in (9) and (10), respectively.
where,, and are the data information contribution, the AWGN component and the interference term received at the subcarrier, respectively.
Information fusion: The FC receives a set of information contribution metrics (i i,k,I i,k ) where i=1,2,⋯,|l k | from the surprisal cameras in the cluster.
If the camera is a surprisal camera, the information contribution vector and matrix (i i,k,I i,k ) are calculated according to (9) and (10).
The locally calculated and received information contribution metrics are then fused together to achieve the estimated global state of the object at time k.
Upon receiving the measurement z i,k, the information contribution matrix I i,k and information contribution vector i i,k are computed as mathbf{I}_{i,k} = mathbf{Y}_{i,k|k-1}mathbf{P}_{mathbf{xz},i,k}mathbf{R}^{-1}_{i,k}mathbf{P}^{T}_{mathbf{xz},i,k}mathbf{Y}^{T}_{i,k|k-1}, (9).
Intuitively, the singularity indicates that the available information is not sufficient for estimation, i.e., the location information contribution in the observation data is not sufficient for deducing a location.
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