Abstract
Problem statement: Target tracking is a challenging application in Wireless Sensor Networks (WSNs) because it is computation-intensive and requires real-time location processing. This study proposes a practical target tracking system based on the Hidden Markov Model in a distributed signal processing framework. In this framework, wireless sensor nodes perform target detection and tracking, whereas target localization requires the collaborative signal processing between wireless sensor nodes for improving the location accuracy and robustness. Approach: For carrying out target tracking under the constraints imposed by the limited transmission capabilities of the wireless sensor nodes, the HMM model and the particle filter approach are adopted in single wireless sensor node due to their outstanding performance and light computational calculations. Furthermore, a progressive multi sensor localization algorithm is proposed in distributed wireless sensor network considering the tradeoff between the localization accuracy of the target and the resource constraints of sensor nodes. Results: Finally, a real world target tracking experiment had been illustrated for static and mobile targets. Here blind child is considered as the target to be tracked within the sensor network. Conclusion: Mathematical analysis and the real world results showed that the target tracking system based on a distributed WSN make efficient use of the communication resources and achieve accurate target tracking successfully.
Highlights
Wireless Sensor Networks (WSN) have become one of the most promising and interesting areas over the past few years
Target Detection done with Hidden Markov Models (HMM) Produces the maximum likelihood estimates via the real time viterbi optimization algorithm
Target Tracking done with Modified Particle Filter (MPF) improves accuracy with the help of the Entropy method
Summary
Wireless Sensor Networks (WSN) have become one of the most promising and interesting areas over the past few years. These networks are very large systems comprised of small sized, low power, low-cost sensor devices which collect information about the physical environment. Due to the low energy constraints in WSN, the network is divided into clusters, each of which will have a cluster-head, which is equipped with a GPS device This minimizes the energy consumption by avoiding all the nodes needing to send data to a distant base station, which is away from the vicinity of the sensor nodes in the target tracking scenario
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