Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Distributed Multi-sensor Multi-view Fusion based on Generalized
  Covariance Intersection   Distributed multi-target tracking (DMTT) is addressed for sensors having
different fields of view (FoVs). The proposed approach is based on the idea of
fusing the posterior Probability Hypotheses Densities (PHDs) generated by the
sensors on the basis of the local measurements. An efficient and robust
distributed fusion algorithm combining the Generalized Covariance Intersection
(GCI) rule with a suitable Clustering Algorithm (CA) is proposed. The CA is
used to decompose each posterior PHD into well-separated components (clusters).
For the commonly detected targets, an efficient parallelized GCI fusion
strategy is proposed and analyzed in terms of $L_1$ error. For the remaining
targets, a suitable compensation strategy is adopted so as to counteract the
GCI sensitivity to independent detections while reducing the occurrence of
false targets. Detailed implementation steps using a Gaussian Mixture (GM)
representation of the PHDs are provided. Numerical experiments clearly confirms
the effectiveness of the proposed CA-GCI fusion algorithm.

15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math