3D position sensing using the differences in the time-of-flights from a wave source to various receivers

Mahajan, Anupama; Walworth, M.

doi:10.1109/70.917087

Cited by 113 publications

(73 citation statements)

References 11 publications

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“…The 3-D source location and origin time were found using a least squares inversion algorithm [Mahajan and Walworth, 2001]. Other inversion schemes [e.g., Salamon and Wiebols, 1974] produced similar results.…”

Section: Ae Locationsmentioning

confidence: 76%

Preslip and cascade processes initiating laboratory stick slip

2014

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Recent modeling studies have explored whether earthquakes begin with a large aseismic nucleation process or initiate dynamically from the rapid growth of a smaller instability in a "cascade-up" process. To explore such a case in the laboratory, we study the initiation of dynamic rupture (stick slip) of a smooth saw-cut fault in a 76 mm diameter cylindrical granite laboratory sample at 40-120 MPa confining pressure. We use a high dynamic range recording system to directly compare the seismic waves radiated during the stick-slip event to those radiated from tiny (M À6) discrete seismic events, commonly known as acoustic emissions (AEs), that occur in the seconds prior to each large stick slip. The seismic moments, focal mechanisms, locations, and timing of the AEs all contribute to our understanding of their mechanics and provide us with information about the stick-slip nucleation process. In a sequence of 10 stick slips, the first few microseconds of the signals recorded from stick-slip instabilities are nearly indistinguishable from those of premonitory AEs. In this sense, it appears that each stick slip begins as an AE event that rapidly (~20 μs) grows about 2 orders of magnitude in linear dimension and ruptures the entire 150 mm length of the simulated fault. We also measure accelerating fault slip in the final seconds before stick slip. We estimate that this slip is at least 98% aseismic and that it both weakens the fault and produces AEs that will eventually cascade-up to initiate the larger dynamic rupture.

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Section: Ae Locationsmentioning

confidence: 76%

Preslip and cascade processes initiating laboratory stick slip

2014

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“…As the inequality between and is forced to be an equality, they are adjusted in a tight manner to estimate because only the square and cross multiplication terms of , which is represented by , in (36) are involved in the optimization process. Nevertheless, instead of employing , after estimating , we substitute the node position estimates, , in (32) and minimize the resultant expression to produce a more accurate estimate of : (39) For its ESDP version, the -dimensional matrix cone relaxation in (35) will be further relaxed to …”

Section: Node Localization With Unknown Propagation Speedmentioning

confidence: 99%

Semi-Definite Programming Algorithms for Sensor Network Node Localization With Uncertainties in Anchor Positions and/or Propagation Speed

Lui

et al. 2009

IEEE Trans. Signal Process.

159

112

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Abstract-Finding the positions of nodes in an ad hoc wireless sensor network (WSN) with the use of the incomplete and noisy distance measurements between nodes as well as anchor position information is currently an important and challenging research topic. However, most WSN localization studies have considered that the anchor positions and the signal propagation speed are perfectly known which is not a valid assumption in the underwater and underground scenarios. In this paper, semi-definite programming (SDP) algorithms are devised for node localization in the presence of these uncertainties. The corresponding Cramér-Rao lower bound (CRLB) is also produced. Computer simulations are included to contrast the performance of the proposed algorithms with the conventional SDP method and CRLB.Index Terms-Node localization, range measurements, semi-definite programming, sensor networks.

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“…It uses concurrent wireless communication and ultrasonic signal to determine the T DOA value between two nodes referring to their own CPU timestamps. Mahajan et al's work [19] uses TDOA measurements to solve a linear equations system similar to ours. Since their TDOAs are measured by CPU timestamps, clock synchronization is needed.…”

Section: Related Workmentioning

confidence: 99%

“…Existing work basically use three types of measurements of acoustic signals: TDOA [24], [19], [32], [9], DOA (direction of arrival) [22], [14], [12], [15] and received signal energy [25], [26], [4], [21], [3].…”

Section: Related Workmentioning

confidence: 99%