Abstract
Data association plays an important role in radar tracking algorithm. The problem of tracking multiple targets is studied in this paper. In order to solve the complicated situation and reduce computation burden because of the multiple tracking environment, an approach has been developed in this paper. This algorithm is implemented with an adaptive filter which consists of a data association technique denoted competitive Hopfield neural network and Kalman filtering to solve both data association and target tracking problems simultaneously. In order to prove the tracking performance, a computer simulation algorithm is proposed in this paper. Because of its computation capability of this algorithm, the radar measurement related to existed target tracks can be chosen optimally. Computer simulation results indicate that this approach successfully and optimally solves the data association problems.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA2005 |
| Editors | T. Roska, B.E. Shi, Z. Chen, C.-T. Lin, C. Rekeczky |
| Pages | 114-117 |
| Number of pages | 4 |
| Publication status | Published - 2005 Oct 31 |
| Event | 9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA - Hsinchu, Taiwan Duration: 2005 May 28 → 2005 May 30 |
Other
| Other | 9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA |
|---|---|
| Country | Taiwan |
| City | Hsinchu |
| Period | 05-05-28 → 05-05-30 |
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All Science Journal Classification (ASJC) codes
- Software
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Applying neural network algorithm to data association technique. / Chung, Y. N.; Chen, H. T.; Juang, D. J.; Chen, J. Y.; Lee, J. R.
Proceedings - 9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA2005. ed. / T. Roska; B.E. Shi; Z. Chen; C.-T. Lin; C. Rekeczky. 2005. p. 114-117.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Applying neural network algorithm to data association technique
AU - Chung, Y. N.
AU - Chen, H. T.
AU - Juang, D. J.
AU - Chen, J. Y.
AU - Lee, J. R.
PY - 2005/10/31
Y1 - 2005/10/31
N2 - Data association plays an important role in radar tracking algorithm. The problem of tracking multiple targets is studied in this paper. In order to solve the complicated situation and reduce computation burden because of the multiple tracking environment, an approach has been developed in this paper. This algorithm is implemented with an adaptive filter which consists of a data association technique denoted competitive Hopfield neural network and Kalman filtering to solve both data association and target tracking problems simultaneously. In order to prove the tracking performance, a computer simulation algorithm is proposed in this paper. Because of its computation capability of this algorithm, the radar measurement related to existed target tracks can be chosen optimally. Computer simulation results indicate that this approach successfully and optimally solves the data association problems.
AB - Data association plays an important role in radar tracking algorithm. The problem of tracking multiple targets is studied in this paper. In order to solve the complicated situation and reduce computation burden because of the multiple tracking environment, an approach has been developed in this paper. This algorithm is implemented with an adaptive filter which consists of a data association technique denoted competitive Hopfield neural network and Kalman filtering to solve both data association and target tracking problems simultaneously. In order to prove the tracking performance, a computer simulation algorithm is proposed in this paper. Because of its computation capability of this algorithm, the radar measurement related to existed target tracks can be chosen optimally. Computer simulation results indicate that this approach successfully and optimally solves the data association problems.
UR - http://www.scopus.com/inward/record.url?scp=27144516736&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=27144516736&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:27144516736
SP - 114
EP - 117
BT - Proceedings - 9th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA2005
A2 - Roska, T.
A2 - Shi, B.E.
A2 - Chen, Z.
A2 - Lin, C.-T.
A2 - Rekeczky, C.
ER -