Accurate Parameter Estimation of Time-varying Nuclear Radiation Field with Mobile Sensors
Bo Chen, Zhicheng Li, Zaiyue Yang · 2021
In this paper, the optimization strategy of mobile sensors and the parameter estimation of time-varying nuclear radiation field are investigated. Based on the measurement model with white Gaussian noise, Fisher information matrix is derived as an information metric. At each time step, finding the best mobile sensor coordinates that contain the amount of maximal information in the 4-Dimension space is formulated as a constrained nonlinear optimization problem, which is able to minimize the trace of Cramer-Rao Lower Bound. Further, an efficient heuristic algorithm called Augmented Lagrangian Genetic Algorithm is adopted to solve the above optimization problem. Then, the parameters of nuclear radiation field are estimated by a maximum likelihood estimator. The proposed sensor coordinates moving strategy has better estimation performance than random coordinates strategy, which is demonstrated via simulation results.