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Determining an optimal emitting source location based on the time of arrival   (TOA) measurements is one of the important problems in Wireless Sensor   Networks (WSNs). The nonlinear least-squares (NLS) estimation technique is   employed to obtain the location of an emitting source. This optimization   problem has been formulated by the minimization of the sum of squared   residuals between estimated and measured data as the objective function. This   paper presents a hybridization of Genetic Algorithm (GA) for the   determination of the global optimum solution with the local search   Newton-Raphson (NR) method. The corresponding Cramer-Rao lower bound (CRLB)   on the localization errors is derived, which gives a lower bound on the   variance of any unbiased estimator. Simulation results under different   signal-to-noise-ratio (SNR) conditions show that the proposed hybrid Genetic   Algorithm-Newton-Raphson (GA-NR) improves the accuracy and efficiency of the   optimal solution compared to the regular GA. [Project of the Serbian Ministry   of Education, Science and Technological Development, Grant no. TR32028

Optimal source localization problem based on TOA measurements