Abstract
In multisensor cooperative detection network, some random disturbances, energy carried by sensor, distance between target and sensor node, and so on all affect the sensor selection scheme. To effectively select some sensors for detecting the target, a novel sensor selection method considering uncertainty disturbance is proposed under constraints of estimation accuracy and energy consumption. Firstly, the sensor selection problem is modeled as a binary form optimization problem with a penalty term to minimize the number of sensors. Secondly, some factors (precision, energy, and distance, etc.) affecting the sensor selection scheme are analyzed and quantified, and energy consumption matrix and estimation precision threshold are given by matrix tra‘nsformation. Finally, the problem of minimizing sensor number after relaxation is solved by convex optimization method, obtaining sensor selection scheme by discretization and legitimization of the suboptimal solution after convex relaxation. Simulation results show that the proposed algorithm can ensure the minimum number of sensors, improving accuracy of state estimation and saving network energy.
Highlights
Wireless Sensor Network (WSN) is a self-organization wireless network composed of large numbers of microsensor nodes
All sensor nodes in WSN can be used to obtain the most comprehensive information related to target; it leads to the energy consumption and processing burden of the network
We give simulation results and analysis on the distribution and number of sensor node selection, besides the estimation accuracy of algorithms with or without disturbance, which are used to describe the performance of the proposed algorithm
Summary
Wireless Sensor Network (WSN) is a self-organization wireless network composed of large numbers of microsensor nodes. Under some conditions including bounded disturbance of sensor measurement and sensor location, a new sensor selection algorithm based on the constraints of energy and estimation accuracy is proposed. By using convex relaxation technology, the minimum number of sensor selection set is obtained, and it balances network energy and measurement accuracy to ensure the performance of the multisensor cooperative detection system. Compared with the traditional method, the number of selected sensors can be effectively reduced (3) The energy consumption matrix and state estimation precision are regarded as constraints of the sensor selection problem; it more reflects various factors of the complex environment (4) We introduce techniques including the convex relaxation, discretization, and legitimization of bounded interval [0,1], which are used to handle Np-hard problem of sensor scheduling and receive suboptimal solution.
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