scholarly journals Modeling Distance and Bandwidth Dependency of TOA-Based UWB Ranging Error for Positioning

2009 ◽  
Vol 2009 ◽  
pp. 1-4 ◽  
Author(s):  
Giovanni Bellusci ◽  
Gerard J. M. Janssen ◽  
Junlin Yan ◽  
Christian C. J. M. Tiberius
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Random Variable ◽  
Estimation Accuracy ◽  
Channel Measurements ◽  
Toa Estimation ◽  
Ranging Error ◽  
The Mean ◽  
Range Error

A statistical model for the range error provided by TOA estimation using UWB signals is given, based on UWB channel measurements between 3.1 and 10.6 GHz. The range error has been modeled as a Gaussian random variable for LOS and as a combination of a Gaussian and an exponential random variable for NLOS. The distance and bandwidth dependency of both the mean and the standard deviation of the range error has been analyzed, and insight is given in the different phenomena which affect the estimation accuracy. A possible application of the model to weighted least squares positioning is finally investigated. Noticeable improvements compared to the traditional least squares method have been obtained.

Calculation of radioimmunoassay standard curves.

1977 ◽  
Vol 23 (9) ◽  
pp. 1624-1627 ◽  
Author(s):  
A J Naus ◽  
P S Kuppens ◽  
A Borst
Keyword(s):  
Least Squares ◽  
Calibration Curve ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Mean Deviation ◽  
Weighted Least Squares Method ◽  
The Mean ◽  
Good Standard

Abstract A method for calculating radioimmunoassay standard curves, based on the theory of Ekins et al., is described. Because a four-parameter model is used, nonlinear standard curves are the result. The calibration curve is fitted to the measured standard points by means of a weighted least-squares method. The program based on this model can be easily processed on a desk-top calculator. For all 250 runs of six different assays, very good standard curves could be obtained. The mean deviation between the concentrations of the standard points and the corresponding calculated values was about 6%. In 26% of the cases it could be shown that the model we describe gave significantly better results than did two simpler ones.

scholarly journals An Egg Volume Measurement System Based on the Microsoft Kinect

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2454 ◽  
Author(s):  
Ting Chan ◽  
Derek Lichti ◽  
Adam Jahraus ◽  
Hooman Esfandiari ◽  
Herve Lahamy ◽  
...  
Keyword(s):  
Least Squares ◽  
Point Cloud ◽  
Least Squares Method ◽  
Point Clouds ◽  
Volume Estimation ◽  
Microsoft Kinect ◽  
Estimation Accuracy ◽  
Shape Parameters ◽  
Post Processing ◽  
Egg Volume

Measuring the volume of bird eggs is a very important task for the poultry industry and ornithological research due to the high revenue generated by the industry. In this paper, we describe a prototype of a new metrological system comprising a 3D range camera, Microsoft Kinect (Version 2) and a point cloud post-processing algorithm for the estimation of the egg volume. The system calculates the egg volume directly from the egg shape parameters estimated from the least-squares method in which the point clouds of eggs captured by the Kinect are fitted to novel geometric models of an egg in a 3D space. Using the models, the shape parameters of an egg are estimated along with the egg’s position and orientation simultaneously under the least-squares criterion. Four sets of experiments were performed to verify the functionality and the performance of the system, while volumes estimated from the conventional water displacement method and the point cloud captured by a survey-grade laser scanner serve as references. The results suggest that the method is straightforward, feasible and reliable with an average egg volume estimation accuracy 93.3% when compared to the reference volumes. As a prototype, the software part of the system was implemented in a post-processing mode. However, as the proposed processing techniques is computationally efficient, the prototype can be readily transformed into a real-time egg volume system.

WAVELET ESTIMATORS FOR LONG MEMORY IN STOCK MARKETS

2009 ◽  
Vol 12 (03) ◽  
pp. 297-317 ◽  
Author(s):  
ANOUAR BEN MABROUK ◽  
HEDI KORTAS ◽  
SAMIR BEN AMMOU
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Stock Returns ◽  
Long Memory ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Estimation Accuracy ◽  
Approximate Maximum Likelihood ◽  
Approximate Maximum Likelihood Estimator ◽  
Wavelet Estimators

In this paper, fractional integrating dynamics in the return and the volatility series of stock market indices are investigated. The investigation is conducted using wavelet ordinary least squares, wavelet weighted least squares and the approximate Maximum Likelihood estimator. It is shown that the long memory property in stock returns is approximately associated with emerging markets rather than developed ones while strong evidence of long range dependence is found for all volatility series. The relevance of the wavelet-based estimators, especially, the approximate Maximum Likelihood and the weighted least squares techniques is proved in terms of stability and estimation accuracy.

A Least-Squares Method for Computing Balance Corrections

1964 ◽  
Vol 86 (3) ◽  
pp. 273-277 ◽  
Author(s):  
Thomas P. Goodman
Keyword(s):  
Least Squares ◽  
Digital Computer ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Rotating Machinery ◽  
Residual Vibration ◽  
Computing Procedure ◽  
Balance Corrections

To compute final correction masses for multispeed, multiplane balancing of rotating machinery, a least-squares computing procedure has been developed. This procedure uses plain least squares to minimize the rms residual vibration of selected points on the machinery foundation, and then uses weighted least squares to reduce the maximum residual vibration. The computations have been programmed for a digital computer.

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