Title :
Exact and Approximate Solutions of Source Localization Problems
Author :
Beck, Amir ; Stoica, Petre ; Li, Jian
fDate :
5/1/2008 12:00:00 AM
Abstract :
We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.
Keywords :
approximation theory; array signal processing; least squares approximations; optimisation; sensor arrays; approximate solution; least squares approach; nonconvex problem; optimization problem; passive sensor array; radiating source localization problem; semidefinite relaxation; squared range-difference measurement; Efficiently and globally optimal solution; generalized trust region subproblems (GTRS); least squares; nonconvex; quadratic function minimization; range measurements; range-difference measurements; single quadratic constraint; source localization; squared range observations;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.909342