BATSE GRB location errors

1998 ◽  
Author(s):  
M. S. Briggs ◽  
G. N. Pendleton ◽  
J. J. Brainerd ◽  
V. Connaughton ◽  
R. M. Kippen ◽  
...  
Keyword(s):  
Location Errors

scholarly journals Mobility-Assisted on-Demand Routing Algorithm for MANETs in the Presence of Location Errors

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Trung Kien Vu ◽  
Sungoh Kwon
Keyword(s):  
Ad Hoc ◽  
Routing Algorithm ◽  
Mobility Prediction ◽  
Location Awareness ◽  
Mobile Nodes ◽  
Location Errors ◽  
On Demand ◽  
Demand Routing ◽  
Hoc Networks ◽  
The Impact

We propose a mobility-assisted on-demand routing algorithm for mobile ad hoc networks in the presence of location errors. Location awareness enables mobile nodes to predict their mobility and enhances routing performance by estimating link duration and selecting reliable routes. However, measured locations intrinsically include errors in measurement. Such errors degrade mobility prediction and have been ignored in previous work. To mitigate the impact of location errors on routing, we propose an on-demand routing algorithm taking into account location errors. To that end, we adopt the Kalman filter to estimate accurate locations and consider route confidence in discovering routes. Via simulations, we compare our algorithm and previous algorithms in various environments. Our proposed mobility prediction is robust to the location errors.

scholarly journals Empirical Analysis and Modeling of Argos Doppler Location Errors in Romania

2018 ◽  
Author(s):  
Laurentiu Rozylowicz ◽  
Florian P. Bodescu ◽  
Cristiana M. Ciocanea ◽  
Athanasios A. Gavrilidis ◽  
Steluta Manolache ◽  
...  
Keyword(s):  
High Speed ◽  
Spatial Ecology ◽  
Local Environment ◽  
Quality Data ◽  
Aquatic Animal ◽  
Location Errors ◽  
Wildlife Tracking ◽  
Doppler Data ◽  
Proper Filter ◽  
And Behavior

ABSTRACTBackgroundAdvances in wildlife tracking technology have allowed researchers to understand the spatial ecology of many terrestrial and aquatic animal species. Argos Doppler is a technology that is widely used for wildlife tracking owing to the small size and low weight of the Argos transmitters. This allows them to be fitted to small-bodied species. The longer lifespan of the Argos units in comparison to units outfitted with miniaturized global positioning system (GPS) technology has also recommended their use. In practice, large Argos location errors often occur due to communication conditions such as transmitter settings, local environment, and the behavior of the tracked individual.MethodsConsidering the geographic specificity of errors and the lack of benchmark studies in Eastern Europe, the research objectives were: (1) to evaluate the accuracy of Argos Doppler technology under various environmental conditions in Romania, (2) to investigate the effectiveness of straightforward destructive filters for improving Argos Doppler data quality, and (3) to provide guidelines for processing Argos Doppler wildlife monitoring data. The errors associated with Argos locations in four geographic locations in Romania were assessed during static, low-speed and high-speed tests. The effectiveness of the Douglas Argos distance angle filter algorithm was then evaluated to ascertain its effect on the minimization of localization errors.ResultsArgos locations received in the tests had larger associated horizontal errors than those indicated by the operator of the Argos system, including under ideal reception conditions. Positional errors were similar to those obtained in other studies outside of Europe. The errors were anisotropic, with larger longitudinal errors for the vast majority of the data. Errors were mostly related to speed of the Argos transmitter at the time of reception, but other factors such as topographical conditions and orientation of antenna at the time of the transmission also contributed to receiving low-quality data. The Douglas-Argos filter successfully excluded the largest errors while retaining a large amount of data when the threshold was set to the local scale (2 km).DiscussionFilter selection requires knowledge about the movement patterns and behavior of the species of interest, and the parametrization of the selected filter typically requires a trial and error approach. Selecting the proper filter reduces the errors while retaining a large amount of data. However, the post-processed data typically includes large positional errors; thus, we recommend incorporating Argos error metrics such as error ellipse or use complex modeling approaches when working with filtered data.

Machining tests for identification of location errors on five-axis machine tools with a tilting head

2015 ◽  
Vol 79 (1-4) ◽  
pp. 245-254 ◽  
Author(s):  
Zhouxiang Jiang ◽  
Xiaoqi Tang ◽  
Xiangdong Zhou ◽  
Shiqi Zheng
Keyword(s):  
Machine Tools ◽  
Location Errors ◽  
Five Axis

Impacts of Plot Location Errors on Accuracy of Mapping and Scaling Up Aboveground Forest Carbon Using Sample Plot and Landsat TM Data

2013 ◽  
Vol 10 (6) ◽  
pp. 1483-1487 ◽  
Author(s):  
Maozhen Zhang ◽  
Hui Lin ◽  
Siqi Zeng ◽  
Jiping Li ◽  
Junnan Shi ◽  
...  
Keyword(s):  
Scaling Up ◽  
Forest Carbon ◽  
Landsat Tm ◽  
Sample Plot ◽  
Location Errors ◽  
Plot Location
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