In the precision positioning system, NLOS(Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and position...In the precision positioning system, NLOS(Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and positioning accuracy. So, in the NLOS environment, it has an important role to eliminate the clock synchronization problem in the positioning system. In order to solve this problem, this paper proposes an improved Kalman filter localization method NLOS-K(Non Line of Sight-Kalman filter). First, the maximum likelihood estimation algorithm is used to iterate. Then, the Kalman filter algorithm is implemented and the Kalman gain matrix is redefined. The clock drift is compensated so that the clock between the master and slave base stations remains synchronized. The experimental results show that in the non-lineof-sight environment, compared with other algorithms, the positioning accuracy error of the improved algorithm is about 5 cm, and the accuracy compared with other algorithms is 97%. In addition, the influence of bandwidth and spectral density on the method is analyzed, and the accuracy and stability of positioning are improved as a whole.展开更多
In order to make up for the deficiencies and insufficiencies that In order to make up for the deficiencies and insufficiencies that wireless sensor network is constituted absolutely by static or dynamic sensor nodes. ...In order to make up for the deficiencies and insufficiencies that In order to make up for the deficiencies and insufficiencies that wireless sensor network is constituted absolutely by static or dynamic sensor nodes. So a deployment mechanism for hybrid nodes barrier coverage (HNBC)is proposed in wireless sensor network, which collaboratively consists of static and dynamic sensor nodes. We introduced the Voronoi diagram to divide the whole deployment area. According to the principle of least square method, and the static nodes are used to construct the reference barrier line (RBL). And we implemented effectively barrier coverage by monitoring whether there is a coverage hole in the deployment area, and then to determine whether dynamic nodes need limited mobility to redeploy the monitoring area. The simulation results show that the proposed algorithm improved the coverage quality, and completed the barrier coverage with less node moving distance and lower energy consumption, and achieved the expected coverage requirements展开更多
文摘In the precision positioning system, NLOS(Non Line of Sight) propagation and clock synchronization error caused by multiple base stations are the main reasons for reducing the reliability of communication and positioning accuracy. So, in the NLOS environment, it has an important role to eliminate the clock synchronization problem in the positioning system. In order to solve this problem, this paper proposes an improved Kalman filter localization method NLOS-K(Non Line of Sight-Kalman filter). First, the maximum likelihood estimation algorithm is used to iterate. Then, the Kalman filter algorithm is implemented and the Kalman gain matrix is redefined. The clock drift is compensated so that the clock between the master and slave base stations remains synchronized. The experimental results show that in the non-lineof-sight environment, compared with other algorithms, the positioning accuracy error of the improved algorithm is about 5 cm, and the accuracy compared with other algorithms is 97%. In addition, the influence of bandwidth and spectral density on the method is analyzed, and the accuracy and stability of positioning are improved as a whole.
文摘In order to make up for the deficiencies and insufficiencies that In order to make up for the deficiencies and insufficiencies that wireless sensor network is constituted absolutely by static or dynamic sensor nodes. So a deployment mechanism for hybrid nodes barrier coverage (HNBC)is proposed in wireless sensor network, which collaboratively consists of static and dynamic sensor nodes. We introduced the Voronoi diagram to divide the whole deployment area. According to the principle of least square method, and the static nodes are used to construct the reference barrier line (RBL). And we implemented effectively barrier coverage by monitoring whether there is a coverage hole in the deployment area, and then to determine whether dynamic nodes need limited mobility to redeploy the monitoring area. The simulation results show that the proposed algorithm improved the coverage quality, and completed the barrier coverage with less node moving distance and lower energy consumption, and achieved the expected coverage requirements
