TY - GEN
T1 - Underwater Long Baseline Positioning Algorithm based on Double-Parameter Constraint
AU - Li, Haoming
AU - Yan, Shefeng
AU - Xu, Lijun
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8/21
Y1 - 2020/8/21
N2 - The uneven underwater terrain and the node motion lead to unpredictable changes in the arrival structure of acoustic signal, and thus the jump in the estimation of the propagation delay of the acoustic signal as well as the 'jump' of the positioning track (JPT) of the long baseline (LBL) positioning system based on the time delay estimation. None of the existing methods can eliminate the jump points completely. In this paper, a new underwater LBL positioning algorithm based on the double-parameter constraint (DPC) is proposed. On the basis of traditional LBL positioning algorithms, a trajectory correction algorithm with double judgement based on the target speed and steering speed parameters is considered. By performing cubic spline interpolation on the positioning points judged as jumps, the impact of jumps of the delay estimation on the final positioning trajectory can be eliminated greatly, thereby reducing positioning errors. Both the simulation analysis and the lake experiments verify the effectiveness of the proposed method.
AB - The uneven underwater terrain and the node motion lead to unpredictable changes in the arrival structure of acoustic signal, and thus the jump in the estimation of the propagation delay of the acoustic signal as well as the 'jump' of the positioning track (JPT) of the long baseline (LBL) positioning system based on the time delay estimation. None of the existing methods can eliminate the jump points completely. In this paper, a new underwater LBL positioning algorithm based on the double-parameter constraint (DPC) is proposed. On the basis of traditional LBL positioning algorithms, a trajectory correction algorithm with double judgement based on the target speed and steering speed parameters is considered. By performing cubic spline interpolation on the positioning points judged as jumps, the impact of jumps of the delay estimation on the final positioning trajectory can be eliminated greatly, thereby reducing positioning errors. Both the simulation analysis and the lake experiments verify the effectiveness of the proposed method.
KW - Kalman filter
KW - arrival structure
KW - long baseline positioning system
KW - matched filter
KW - trajectory correction
UR - http://www.scopus.com/inward/record.url?scp=85097960668&partnerID=8YFLogxK
U2 - 10.1109/ICSPCC50002.2020.9259528
DO - 10.1109/ICSPCC50002.2020.9259528
M3 - Conference contribution
AN - SCOPUS:85097960668
T3 - ICSPCC 2020 - IEEE International Conference on Signal Processing, Communications and Computing, Proceedings
BT - ICSPCC 2020 - IEEE International Conference on Signal Processing, Communications and Computing, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2020
Y2 - 21 August 2020 through 23 August 2020
ER -