TY - JOUR
T1 - Interference Striation Based Particle Filter Tracking for Target Depth in the Reliable Acoustic Path
AU - Guo, Yue
AU - Duan, Rui
AU - Yang, Kunde
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Effective real-time estimation of target depth trajectory is an important issue in target detection. This paper proposes a target depth tracking method based on particle filter in the reliable acoustic path. The proposed method utilizes the Lloyd mirror interference to model the measurement equation as a function of the acoustic power spectrum varying with the target depth. The notable feature of the method is the use of analytical expressions of measurement equations to improve efficiency. The method is successfully verified by experimental data, and the result proves the effectiveness of the method in target depth tracking.
AB - Effective real-time estimation of target depth trajectory is an important issue in target detection. This paper proposes a target depth tracking method based on particle filter in the reliable acoustic path. The proposed method utilizes the Lloyd mirror interference to model the measurement equation as a function of the acoustic power spectrum varying with the target depth. The notable feature of the method is the use of analytical expressions of measurement equations to improve efficiency. The method is successfully verified by experimental data, and the result proves the effectiveness of the method in target depth tracking.
KW - particle filter
KW - target depth tracking
KW - the reliable acoustic path
UR - http://www.scopus.com/inward/record.url?scp=85131699843&partnerID=8YFLogxK
U2 - 10.1109/OCEANSChennai45887.2022.9775265
DO - 10.1109/OCEANSChennai45887.2022.9775265
M3 - 会议文章
AN - SCOPUS:85131699843
SN - 0197-7385
JO - Oceans Conference Record (IEEE)
JF - Oceans Conference Record (IEEE)
T2 - OCEANS 2022 - Chennai
Y2 - 21 February 2022 through 24 February 2022
ER -