TY - GEN
T1 - A maneuvering tracking method based on LSTM and CS model
AU - Li, Siwei
AU - Hu, Cheng
AU - Wang, Rui
AU - Zhou, Chao
AU - Yang, Jing
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Maneuvering target tracking is an important research field in radar tracking. In recent years, the development of machine learning provides a new idea for maneuvering target tracking. This paper presents a trajectory recognition method based on LSTM (Long Short-Term Memory) and a maneuvering tracking method using matched CS (current statistics) model parameter. This method makes use of the characteristics of LSTM that can effectively combine the above information to realize the recognition of target motion states. Then, clustering analysis is used to obtain the optimal filtering parameters of each motion mode in the statistical sense, and filtering is carried out according to the recognition results of LSTM. Compared with the traditional maneuvering tracking method, this method can maintain stable filtering gain in the duration of maneuvering, and the filtering accuracy is improved.
AB - Maneuvering target tracking is an important research field in radar tracking. In recent years, the development of machine learning provides a new idea for maneuvering target tracking. This paper presents a trajectory recognition method based on LSTM (Long Short-Term Memory) and a maneuvering tracking method using matched CS (current statistics) model parameter. This method makes use of the characteristics of LSTM that can effectively combine the above information to realize the recognition of target motion states. Then, clustering analysis is used to obtain the optimal filtering parameters of each motion mode in the statistical sense, and filtering is carried out according to the recognition results of LSTM. Compared with the traditional maneuvering tracking method, this method can maintain stable filtering gain in the duration of maneuvering, and the filtering accuracy is improved.
KW - CS model
KW - Long Short-Term Memory
KW - maneuvering target tracking
KW - trajectory recognition
UR - http://www.scopus.com/inward/record.url?scp=85091929012&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP47821.2019.9173187
DO - 10.1109/ICSIDP47821.2019.9173187
M3 - Conference contribution
AN - SCOPUS:85091929012
T3 - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
BT - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Y2 - 11 December 2019 through 13 December 2019
ER -