Sensor network basically has many intrinsic limitations such as energy consumption, sensor coverage and connectivity, and sensor processing capability. Tracking a moving target in clusters of sensor network online wit...Sensor network basically has many intrinsic limitations such as energy consumption, sensor coverage and connectivity, and sensor processing capability. Tracking a moving target in clusters of sensor network online with less complexity algorithm and computational burden is our ultimate goal. Particle filtering (PF) technique, augmenting handoff and K-means classification of measurement data, is proposed to tackle the tracking mission in a sensor network. The handoff decision, an alternative to multi-hop transmission, is implemented for switching between clusters of sensor nodes through received signal strength indication (RSSI) measurements. The measurements being used in particle filter processing are RSSI and time of arrival (TOA). While non-line-of-sight (NLOS) is the dominant bias in tracking estimation/accuracy, it can be easily resolved simply by incorporating K-means classification method in PF processing without any priori identification of LOS/NLOS. Simulation using clusters of sensor nodes in a sensor network is conducted. The dependency of tracking performance with computational cost versus number of particles used in PF processing is also investigated.展开更多
Based on the analysis of CDMA handoff, an improved two threshold soft handoff scheme is proposed and analyzed in detail theoretically. Combining with the minimum dwelling time method, we propose a hybrid handof...Based on the analysis of CDMA handoff, an improved two threshold soft handoff scheme is proposed and analyzed in detail theoretically. Combining with the minimum dwelling time method, we propose a hybrid handoff scheme and compare its performance with that of conventional guard channel scheme and minimum dwelling time scheme, respectively. Results show that the suggested scheme is of good performance.展开更多
文摘Sensor network basically has many intrinsic limitations such as energy consumption, sensor coverage and connectivity, and sensor processing capability. Tracking a moving target in clusters of sensor network online with less complexity algorithm and computational burden is our ultimate goal. Particle filtering (PF) technique, augmenting handoff and K-means classification of measurement data, is proposed to tackle the tracking mission in a sensor network. The handoff decision, an alternative to multi-hop transmission, is implemented for switching between clusters of sensor nodes through received signal strength indication (RSSI) measurements. The measurements being used in particle filter processing are RSSI and time of arrival (TOA). While non-line-of-sight (NLOS) is the dominant bias in tracking estimation/accuracy, it can be easily resolved simply by incorporating K-means classification method in PF processing without any priori identification of LOS/NLOS. Simulation using clusters of sensor nodes in a sensor network is conducted. The dependency of tracking performance with computational cost versus number of particles used in PF processing is also investigated.
文摘Based on the analysis of CDMA handoff, an improved two threshold soft handoff scheme is proposed and analyzed in detail theoretically. Combining with the minimum dwelling time method, we propose a hybrid handoff scheme and compare its performance with that of conventional guard channel scheme and minimum dwelling time scheme, respectively. Results show that the suggested scheme is of good performance.
