Exact and approximate route set generation for resilient partial observability in sensor location problems

Metric Multidimensional Scaling is commonly used to solve multi-sensor location problems in 2D or 3D spaces. In this paper, we show that such technique provides poor results in the case of indoor location problems based on 802.11 Fine Timing Measurements, because the number of anchors is small and the ranging error asymmetrically distributed. We then propose a two-step iterative approach based on geometric resolution of angle inaccuracies. The first step reduces the effect of poor ranging exchanges. The second step reconstructs the anchor positions, starting from the distances of highest likely-accuracy. We show that this geometric approach provides better location accuracy results than other Euclidean Distance Metric techniques based on Least Square Error logic. We also show that the proposed technique, with the input of one or more known location, can allow a set of fixed sensors to auto-determine their position on a floor plan.

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Optimal sensor location problems

Modeling, Estimation, and Their Applications for Distributed Parameter Systems - Lecture Notes in Control and Information Sciences ◽

10.1007/bfb0112548 ◽

2007 ◽

pp. 216-242

Keyword(s):

Location Problems ◽

Sensor Location ◽

Optimal Sensor Location

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Heuristics for Mixed Strength Sensor Location Problems

International Journal of Operations Research and Information Systems ◽

10.4018/ijoris.2020040104 ◽

2020 ◽

Vol 11 (2) ◽

pp. 53-65

Author(s):

Rex K Kincaid ◽

Robin M. Givens

Keyword(s):

Environmental Conditions ◽

Location Problems ◽

Minimum Size ◽

Geometric Graphs ◽

Illegal Logging ◽

Sensor Location ◽

Rain Forests ◽

Solution Quality ◽

Location Detection ◽

Location Sensor

Location-detection problems are pervasive. Examples include the detection of faults in microprocessors, the identification of contaminants in ventilation systems, and the detection of illegal logging in rain forests. In each of these applications a network provides a convenient modelling paradigm. Sensors are placed at particular node locations that, by design, uniquely detect and locate issues in the network. Open locating-dominating (OLD) sets constrain a sensor's effectiveness by assuming that it is unable to detect problems originating from the sensor location. Sensor failures may be caused by extreme environmental conditions or by the act of a nefarious individual. Determining the minimum size OLD set in a network is computationally intractable, but can be modelled as an integer linear program. The focus of this work is the development and evaluation of heuristics for the minimum OLD set problem when sensors of varying strengths are allowed. Computational experience and solution quality are reported for geometric graphs of up to 150 nodes.

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