Referenced Items are not available for this document.
In this paper, sequential track correlation algorithm in a multisensor data fusion system is presented. It is well known that the state estimates obtained from a Kalman filter have correlated errors in time. While the innovations are white, this does not carry over to the state estimation errors. It should also be pointed out that the use of a sliding window for track-to-track association with the (appropriate) caveat that the distribution of the sum of chi-square variables over the window is only approximately chi-square distributed.
Published in:
Aerospace and Electronic Systems, IEEE Transactions on
(Volume:44
,
Issue:
1
)
Date of Publication: January 2008
- Page(s):
- 396
- ISSN :
- 0018-9251
- INSPEC Accession Number:
- 9943781
- Digital Object Identifier :
- 10.1109/TAES.2008.4517016
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 12 May 2008
- Issue Date :
- January 2008
- Sponsored by :
- Aerospace & Electronic Systems Society
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