A Quadratically Constrained Fractional Quadratic Programming Approach for Dilution of Precision Minimization
نویسندگان
چکیده
An approach to find the global optimal solution of the dilution of precision (DOP) problem is presented. The DOP optimization problem considered assumes an environment comprising multiple randomly pre-deployed sensors (or navigation sources) and an additional sensor is to be introduced at the location that minimizes variations of the DOP problem (e.g., weighted geometric DOP (WGDOP), horizontal DOP (HDOP), vertical DOP (VDOP), etc.). It is shown that the DOP problem can be formulated as quadratically constrained fractional quadratic program. An algorithm for solving this program is presented an Monte Carlo simulation results are given demonstrating convergence of the proposed approach to the global optimal solution. Additionally, Monte Carlo simulation results are presented, demonstrating the superiority of the proposed algorithm to nonlinear numerical optimization solvers that often converge to local optima.
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