Abstract
An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.
| Original language | English |
|---|---|
| Pages (from-to) | 876-887 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Aerospace and Electronic Systems |
| Volume | 26 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 1990 Sep |
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All Science Journal Classification (ASJC) codes
- Aerospace Engineering
- Electrical and Electronic Engineering
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Extended Solution To Multiple Maneuvering Target Tracking. / Chung, Y. N.; Gustafson, D. L.; Emre, E.
In: IEEE Transactions on Aerospace and Electronic Systems, Vol. 26, No. 5, 09.1990, p. 876-887.Research output: Contribution to journal › Article
TY - JOUR
T1 - Extended Solution To Multiple Maneuvering Target Tracking
AU - Chung, Y. N.
AU - Gustafson, D. L.
AU - Emre, E.
PY - 1990/9
Y1 - 1990/9
N2 - An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.
AB - An improved algorithm for tracking multiple maneuvering targets is presented. This approach is implemented with an approximate adaptive filter consisting of the 1-step conditional maximumlikelihood technique together with the extended Kalman filter and an adaptive maneuvering compensator. In order to avoid the extra computational burden of considering events with negligible probability, a validation matrix is defined in the tracking structure. Via this approach, both data association and target maneuvering problems can be solved simultaneously Detailed Monte-Carlo simulations of the algorithm for many tracking situations are described. Computer simulation results indicate that this approach successfully tracks multiple maneuvering targets over a wide range of conditions.
UR - http://www.scopus.com/inward/record.url?scp=0025493210&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0025493210&partnerID=8YFLogxK
U2 - 10.1109/7.102720
DO - 10.1109/7.102720
M3 - Article
AN - SCOPUS:0025493210
VL - 26
SP - 876
EP - 887
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
SN - 0018-9251
IS - 5
ER -