In this paper, a range-free, passive, and autonomous underwater vehicle (AUV)-based localization scheme is proposed for underwater acoustic sensor networks. The AUV has used four directional acoustic beams with fixed steering angle and width, which led to the constant ratio of array size to wavelength, in order to localize the sensor nodes. The AUV was moved on a random waypoint path and broadcasted messages periodically. The sensor nodes used two successively received message sequences which were submitted by two beams on one side of the AUV path in order to localize themselves. Extensive simulation results in MATLAB demonstrated that using the proposed localization scheme could yield better localization success than other AUV-based localization methods.
In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error. ARTICLE HISTORY
This paper proposes a range-free localization scheme for Underwater Acoustic Sensor Networks (UW-ASNs) that uses an Autonomous Underwater Vehicle (AUV) equipped with a directional transceiver. In this scheme, AUV transmits its current position as it moves over sensors deployment area. Consequently each sensor node receives some signals. By measuring the received signals power and comparing them, the signal with maximum power can be found and its corresponding coordinate can be registered. Major advantage of this method is being robust against the loss of some signals as arrival time and exit time of AUV at communication range of the sensor nodes. Another feature of this localization method is being passive that results in energy-efficiency, and no need to time synchronization and distance estimation among the sensor nodes. Performance of the proposed localization method is evaluated by simulations using MATLAB. Simulation results show that the proposed method can localize more sensors with acceptable error than the other schemes.
The technology of underwater wireless acoustic sensor networks (UWSNs) plays an important role in many commercial and military applications in underwater. In UWSNs, there exist many challenges posed by the specific characteristics of underwater acoustic channel, such as sound propagation speed is a function of depth with unknown parameters. Besides, time synchronization of anchor nodes is a crucial part of the applicable network. Time synchronization of anchor nodes as well as estimation of sound speed parameters considering an isogradient profile is explored here. While the previous efforts do not take into account these factors, this article assumes only one synchronized anchor node in the network and enables joint synchronization of the other anchor nodes and the estimation of the propagation delays between the anchor nodes using a weighted linear least square solution. Then, it uses the estimated propagation delays to estimate the unknown parameters of the sound speed profile using a conventional Gauss‐Newton algorithm with approximately three iterations to converge. Validation of the proposed method is done by the numerical simulations and to demonstrate the effectiveness of the proposed method we compare the results with Cramer‐Rao bound average.
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