Saeed Mohammadloo

Work place: Department of Electrical Engineering, Malek Ashtar University of Technology, Tehran, Iran



Research Interests: Computer systems and computational processes, Data Structures and Algorithms, Control Theory


Saeed Mohammadloo (September 1983), male, Khoy, Iran, research engineer, Malek-e-Ashtar University. His research interests are in the areas of autonomous robots, navigation, data fusion, Intelligent Control and Multivariable Control Theory.

Author Articles
Fusion-Based Sensor Selection for Optimal State Estimation and Minimum Cost (Intelligent Optimization Approach)

By Saeed Mohammadloo Ali Jabar Rashidi

DOI:, Pub. Date: 8 Apr. 2012

This paper proposes a heuristic method for the sensor selection problem that uses a state vector fusion approach as a data fusion method. We explain the heuristic to estimate a stationary target position. Given a first sensor with specified accuracy and by using genetic algorithm, the heuristic selects second sensor such that the fusion of two sensor measurements would yield an optimal estimation in a target localization scenario. Optimality in our method means that a trade-off between estimation error and cost of sensory system should be created. The heuristic also investigates the importance of proportion between the range and bearing measurement accuracy of selected sensor. Monte Carlo Simulation results for a target position estimation scenario showed that the error in heuristic is less than the estimate error where sensors are used alone for estimation, while considering the trade-off between cost and accuracy.

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