1,295 research outputs found
Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks
Accurate localization for mobile nodes has been an important and fundamental
problem in underwater acoustic sensor networks (UASNs). The detection
information returned from a mobile node is meaningful only if its location is
known. In this paper, we propose two localization algorithms based on color
filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively
accomplishing accurate localization of underwater mobile nodes with minimum
energy expenditure. They both adopt the overlapping signal region of task
anchors which can communicate with the mobile node directly as the current
sampling area. PCFL employs the projected distances between each of the task
projections and the mobile node, while ACFL adopts the direct distance between
each of the task anchors and the mobile node. Also the proportion factor of
distance is proposed to weight the RGB values. By comparing the nearness
degrees of the RGB sequences between the samples and the mobile node, samples
can be filtered out. And the normalized nearness degrees are considered as the
weighted standards to calculate coordinates of the mobile nodes. The simulation
results show that the proposed methods have excellent localization performance
and can timely localize the mobile node. The average localization error of PCFL
can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table
Low cost underwater acoustic localization
Over the course of the last decade, the cost of marine robotic platforms has
significantly decreased. In part this has lowered the barriers to entry of
exploring and monitoring larger areas of the earth's oceans. However, these
advances have been mostly focused on autonomous surface vehicles (ASVs) or
shallow water autonomous underwater vehicles (AUVs). One of the main drivers
for high cost in the deep water domain is the challenge of localizing such
vehicles using acoustics. A low cost one-way travel time underwater ranging
system is proposed to assist in localizing deep water submersibles. The system
consists of location aware anchor buoys at the surface and underwater nodes.
This paper presents a comparison of methods together with details on the
physical implementation to allow its integration into a deep sea micro AUV
currently in development. Additional simulation results show error reductions
by a factor of three.Comment: 73rd Meeting of the Acoustical Society of Americ
A survey of localization in wireless sensor network
Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network
Position and Orientation Estimation of a Rigid Body: Rigid Body Localization
Rigid body localization refers to a problem of estimating the position of a
rigid body along with its orientation using anchors. We consider a setup in
which a few sensors are mounted on a rigid body. The absolute position of the
rigid body is not known, but, the relative position of the sensors or the
topology of the sensors on the rigid body is known. We express the absolute
position of the sensors as an affine function of the Stiefel manifold and
propose a simple least-squares (LS) estimator as well as a constrained total
least-squares (CTLS) estimator to jointly estimate the orientation and the
position of the rigid body. To account for the perturbations of the sensors, we
also propose a constrained total least-squares (CTLS) estimator. Analytical
closed-form solutions for the proposed estimators are provided. Simulations are
used to corroborate and analyze the performance of the proposed estimators.Comment: 4 pages and 1 reference page; 3 Figures; In Proc. of ICASSP 201
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