A New Adaptive Method for Target Tracking in Wireless Sensor Networks

Abstract

These days mobile target tracking is considered as one of the important applications of wireless sensor networks. In this regard, the clustering structure is one of the most applicable network structures. In this paper, we suggested a new method for target tracking that makes adaptation with target mobility model. This method utilizes two tools to create adaptability which are changing the size and shape of clusters according to target mobility model. Also by combining static and dynamic clustering a semi dynamic clustering structure has been developed to implement these tools. Simulation results show that our suggested method decreases both energy consumption by decreasing clusters size when the target moves uniformly, and tracking error by changing the size and the shape of clusters according to target mobility when the target moves unpredictably. General TermsSemi-Dynamic clustering, target tracking, tracking error.

A New Adaptive Target Tracking Protocol in Wireless Sensor Networks

“…The consumed energy by a member node to transmit l bit message to a cluster head based on is the distance between each CH1 and CH2. 2 …”

“…As it was mentioned before, the CH2 node is selected among the CH1 nodes and according to paper [2], if assume the neighborhood degree of each CH1 node is q, then the number of message interchanges between CH1 nodes for introduction of CH2 node, Num, is estimated as:…”

“…After receiving information from member nodes in backbone clusters, CH1 nodes transmit their integrated information to CH2. Subsequently, after receiving this information from all of CH1 nodes, CH2 transmits its integrated information to the base station [2]. Fig.…”

“…In [8], based on the uniform sampling intervals, a covariance control framework is presented where the tracking accuracy is defined as an expected covariance matrix, and multiple tasking sensors for the next time step are selected such that the updated estimation covariance will be within the desirable covariance at all times. In general, most of the previous adaptive target tracking protocols(like AEC in [6], PATES in [4], T 2 BM 2 in [2] ), have focused on the adaptive sampling time interval or adaptive wakening up areas separately, but in this paper a new protocol has been presented that have pained attention on both of the subjects. In other words, in this paper a new Adaptive Target Tracking Protocol (ATTP) has been proposed which at each time step, employs two helpful tools.…”

“…Some of them have focused on adaptive sampling time intervals and some of them tried to adapt the size of wakening up areas. For example, in paper [2] a new method that is called Target Tracking Based on Mobility Model (T 2 BM 2 ) has been proposed, which uses Semi-Dynamic clustering (SDC) structure. The main idea of this method is that when the target moves randomly, to increase the accuracy of tracking it is better to use bigger size of clusters.…”