Multipath effects and turbulence in shallow sea environments can degrade the accuracy of sensor data

affecting the precision of autonomous underwater vehicle(AUV)trajectory tracking.To address this problem

an improved firefly algorithm optimized unscented particle filter(IFA-UPF)underwater target tracking algorithm

which integrates unscented Kalman filter(UKF)and firefly algorithm(FA)based on particle filter(PF)framework

is proposed.The algorithm generates prediction particles through UKF to enhance the precision of the importance function

replaces resampling with an IFA to avoid particle impoverishment

and guides particle movement towards global optimality to improve estimation precision.Simulation results show that the IFA-UPF algorithm achieves more accurate tracking of AUVs than traditional UKF and PF algorithms

with smaller tracking errors.This algorithm optimizes sensor data processing and significantly enhances the reliability and effectiveness of AUV trajectory tracking in complex environments

demonstrating broad application potential.