Abstract
In this article, we consider the sensor selection problem of choosing [Formula: see text] sensors from a set of [Formula: see text] possible sensor measurements. The sensor selection problem is a combinational optimization problem. Evaluating the performance for each possible combination is impractical unless [Formula: see text] and [Formula: see text] are small. We relax the original selection problem to be a convex optimization problem and describe a projected gradient method with Barzilai–Borwein step size to solve the proposed relaxed problem. Numerical results demonstrate that the proposed algorithm converges faster than some classical algorithms. The solution obtained by the proposed algorithm is closer to the truth.
Highlights
With the wide application of sensor networks in many fields,[1,2,3,4,5,6,7,8] all kinds of technologies related to sensor networks have been highly concerned by researchers
Due to the limited energy of sensors themselves, unnecessary energy consumption caused by communication and information processing will lead to premature paralysis of sensor networks
We report the numerical results of the proposed projected gradient methods for sensor selection problems in this article
Summary
With the wide application of sensor networks in many fields (robotics, target tracking, medical health monitoring, traffic control, etc.),[1,2,3,4,5,6,7,8] all kinds of technologies related to sensor networks have been highly concerned by researchers. When sensor networks are used for target tracking, sensors communicate and process information for tracking targets. Due to the limited energy of sensors themselves, unnecessary energy consumption caused by communication and information processing will lead to premature paralysis of sensor networks. Excessive use of a few sensor nodes to track the target leads to the exposure of the node, which is attacked by the enemy (such as the radar sensor network). In order to reduce the energy consumption of sensor nodes and increase the concealment, it is necessary to study the sensor selection problems.
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