In this article, the multistatic localization problem with unknown propagation speed is investigated using differential delays and Doppler shifts between the signals from direct and indirect paths. A series of pseudolinear equations is formulated via the transformation of measurement models. A weighted least squares (WLS) formulation is then proposed after ignoring the second-order error terms, which can be rewritten as a nonconvex optimization problem with the relationships among variables included as constraints. To deal with the nonconvexity of the problem, semidefinite relaxation is applied, resulting in a convex semidefinite program (SDP). Several reasonable second-order cone constraints constructed via basic inequality and Cauchy–Schwarz inequality are added to tighten the relaxed SDP problem. By preserving the second-order error terms in equations, the bias of the estimate from the WLS formulation is also derived and then subtracted to nearly eliminate the bias and reach a bias-reduced solution. Simulation results show that the mean square error of the proposed method approaches the Cramer–Rao lower bound, and the bias is reduced significantly.
A Bias-Reduced Solution for Multistatic Localization Using Differential Delays and Doppler Shifts
IEEE Transactions on Aerospace and Electronic Systems ; 59 , 5 ; 5120-5133
01.10.2023
1239406 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch