A Passive Localization Method of Underwater Multi-Sensor Systems with Unknown Source Frequency Based on Joint Estimation

This study introduces an innovative passive localization algorithm tailored for underwater multi-sensor AOA-TDOA-FDOA joint localization challenges where the radiated frequency of the target acoustic source is unknown. The algorithm is designed to concurrently estimate the position, velocity, and signal frequency of the sound source. Initially, a weighted least squares approach is applied, incorporating auxiliary variables to convert the nonlinear observation equations into pseudo-linear forms, thus obtaining preliminary estimates of the source parameters. Subsequently, a new optimization model is developed based on the relationship between the auxiliary variables and the estimated quantities, and this model is solved to refine the estimates. Experimental results indicate that the proposed algorithm achieves root mean square errors (RMSE) for position and velocity estimation that are consistent with the Cramér-Rao Lower Bound (CRLB), even in scenarios where the sound source frequency is unknown.