Underwater TDOA/FDOA joint localization method based on Taylor-weighted least squares algorithm

Aiming at the problem of inaccurate localization caused by the two-stage weighted least squares algorithm ignoring the noise square term in the complex underwater localization scene, this paper proposes an underwater TDOA/FDOA joint localization method based on the Taylor-weighted least squares algorithm. This method first solves the rough estimated position and velocity of the target through the weighted least squares algorithm. Then constructs the localization error equation by solving the Taylor expansion of the TDOA /FDOA measurement values, and continuously updates the estimated position and velocity of the target by an iterative method. Finally, when the localization error is small enough or the maximum number of iterations is reached, the algorithm stops running and outputs the estimated target position and velocity. Simulation shows that when the noise variance is less than 10 decibels, the root mean square error of the position and velocity estimation of the algorithm in this paper can be close to or approximately equal to the Cramer-rao lower bound.