Research On Node Cooperative Mobile Scheduling Algorithm Based On Target Tracking In WSN

The moving target tracking algorithm in wireless sensor network(Wireless Sensor Network,WSN)needs to ensure high tracking accuracy without consuming too much energy.Efficient tracking effect requires dispatching more mobile sensors,but mobile sensors will generate a lot of energy consumption.Therefore,how to balance the contradiction between tracking accuracy and network consumption and design a reasonable node collaborative scheduling algorithm is the key issue for target tracking in WSN.Therefore,this paper analyzes the research background and research status in this field,and then proposes a node coordinated scheduling mobile tracking algorithm for mobile target tracking.This paper proposes a two-layer fuzzy tree moving target tracking strategy based on Cuckoo's algorithm.The target is regarded as a "target circle",so that mobile sensors are dispatched to track the target.The strategy is composed of a strategy decision-making layer,a tracking strategy and a diffusion strategy.The strategy decision-making layer can select the best strategy at the current moment according to the situation of each node,that is,execute the tracking strategy or the diffusion strategy.The tracking strategy reasonably schedules the mobile sensors according to the position of the sensor nodes and the "target circle",and the diffusion strategy is to spread the nodes apart when the sensors are too dense.Since the trajectory of a moving target in reality is not necessarily traceable,this article uses a "target circle" to represent the target,without the need to predict the target position.The two-layer fuzzy logic tree can find the best scheduling scheme for sensor nodes,and realize the coordinated scheduling for moving targets.The simulation results show that this method can improve tracking performance.Good tracking results can be obtained when two mobile sensors are dispatched,and good coverage and tracking performance can be guaranteed when 40 sensors are deployed.The performance of the algorithm is analyzed by comparing various parameters through simulation experiments.The simulation results show that the double-layer fuzzy tree moving target tracking strategy based on the cuckoo algorithm reduces the calculation time by 20% and the tracking error by 25%compared with the genetic fuzzy tree algorithm.The accuracy is increased by about 50%.This paper proposes an effective hybrid WSN target tracking scheme,which dynamically schedules mobile sensor nodes and static sensor nodes to avoid excessive energy consumption caused by excessive wake-up of static nodes.In addition,a target loss recovery mechanism is proposed,which can find the lost target and wake up fewer static sensor nodes to resume tracking.In order to improve the robustness and accuracy of the recovery mechanism,this paper proposes an Adaptive Unscented Kalman Filter(AUKF)algorithm to dynamically adjust the process noise covariance.The simulation results show that even when the target is lost,the hybrid WSN target tracking scheme can not only track the target effectively,but also maintain excellent accuracy and robustness with fewer active nodes.The simulation results show that the tracking accuracy of the recovery mechanism with AUKF is about 45% better than the recovery mechanism using Unscented Kalman Filter(UKF)in the tracking process.Among the above two tracking strategies,the two-layer fuzzy tree moving target tracking strategy based on the cuckoo algorithm regards the moving target as a dynamic "target circle",which does not include the prediction of the target trajectory;and the hybrid based on dynamic clusters WSN moving target tracking strategy involves the prediction of target trajectory and the recovery mechanism of target loss.The correlation between the two technical points is that two different technical methods are used to effectively and reasonably schedule static nodes and dynamic nodes to track moving targets.