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On the statistical errors of RADAR location sensor networks with built-in Wi-Fi Gaussian linear fingerprints.

Zhou M, Xu YB, Ma L, Tian S - Sensors (Basel) (2012)

Bottom Line: However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern.Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments.Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

View Article: PubMed Central - PubMed

Affiliation: Communication Research Center, School of Electronics and Information Engineering, Harbin Institute of Technology, Nangang District, Harbin, Heilongjiang, China. mzhou@hit.edu.cn

ABSTRACT
The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

No MeSH data available.


Optimal means and standard deviations in Gaussian fitting models at TPs.
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f13-sensors-12-03605: Optimal means and standard deviations in Gaussian fitting models at TPs.

Mentions: For consistency to our previous mathematical model, the positions of TP (with +’s) are randomly selected in this straight corridor environment. As shown in Figures 13 and 14, the RSS distributions at the TPs (100 new recorded RSS samples per TP) are fitted well by the Gaussian models with small fitting errors , where, and denote the real recorded and fitted probabilities of sample . Ef is calculated by the expectation of the probability difference of and . Moreover, the RSS samples are recorded by a laptop (ASUS A8F) with our developed RSS sensing software “HITWLAN v1.0” [32] in Figure 15.


On the statistical errors of RADAR location sensor networks with built-in Wi-Fi Gaussian linear fingerprints.

Zhou M, Xu YB, Ma L, Tian S - Sensors (Basel) (2012)

Optimal means and standard deviations in Gaussian fitting models at TPs.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376608&req=5

f13-sensors-12-03605: Optimal means and standard deviations in Gaussian fitting models at TPs.
Mentions: For consistency to our previous mathematical model, the positions of TP (with +’s) are randomly selected in this straight corridor environment. As shown in Figures 13 and 14, the RSS distributions at the TPs (100 new recorded RSS samples per TP) are fitted well by the Gaussian models with small fitting errors , where, and denote the real recorded and fitted probabilities of sample . Ef is calculated by the expectation of the probability difference of and . Moreover, the RSS samples are recorded by a laptop (ASUS A8F) with our developed RSS sensing software “HITWLAN v1.0” [32] in Figure 15.

Bottom Line: However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern.Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments.Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

View Article: PubMed Central - PubMed

Affiliation: Communication Research Center, School of Electronics and Information Engineering, Harbin Institute of Technology, Nangang District, Harbin, Heilongjiang, China. mzhou@hit.edu.cn

ABSTRACT
The expected errors of RADAR sensor networks with linear probabilistic location fingerprints inside buildings with varying Wi-Fi Gaussian strength are discussed. As far as we know, the statistical errors of equal and unequal-weighted RADAR networks have been suggested as a better way to evaluate the behavior of different system parameters and the deployment of reference points (RPs). However, up to now, there is still not enough related work on the relations between the statistical errors, system parameters, number and interval of the RPs, let alone calculating the correlated analytical expressions of concern. Therefore, in response to this compelling problem, under a simple linear distribution model, much attention will be paid to the mathematical relations of the linear expected errors, number of neighbors, number and interval of RPs, parameters in logarithmic attenuation model and variations of radio signal strength (RSS) at the test point (TP) with the purpose of constructing more practical and reliable RADAR location sensor networks (RLSNs) and also guaranteeing the accuracy requirements for the location based services in future ubiquitous context-awareness environments. Moreover, the numerical results and some real experimental evaluations of the error theories addressed in this paper will also be presented for our future extended analysis.

No MeSH data available.