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New Real Time Location Sensing System Using Direction of Arrival Based Multilateration Technique


Affiliations
1 Department of Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India
2 Department of Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India
     

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Real Time Location Sensing (RTLS) for indoor location estimation is an emerging technology. The challenging issues of this technology are finding the exact coordinates of the object with less number of RFID (Radio Frequency Identification) tags and also solving the over-deterministic equations. The existing techniques such as ML (Maximum Likelihood), ESPRIT (Estimated Signal Parameters via Rotational Invariance) find only the DOA (Direction of Arrival) of the signal and they apply only to special structure arrays. The existing localisation techniques such as triangulation, trilateration can solve the equations non linearly and hence have high degree of computational complextiy. To solve this problem, a new DOA based multilateration localisation technique have been proposed and their performances are analysed. In this approach, the position of the stationary object is determined by using Music based DOA and the localisation technique called MULTILATERATION. In this proposed DoA based multilateration technique, the nonlinear equations have been solved linearly which decreases the complexity of the proposed technique than the existing algorithms.  Since, the reference tags are placed only in the desired direction using DoA estimation, the number of reference tags required for the accurate estimation of location is significantly reduced than the existing techniques.


Keywords

Degree of Solvability, Direction of Arrival, Multilateration, Multiple Signal Classification, Real Time Location Sensing, Signal to Noise Ratio, Spatial Spectrum, Time Difference of Arrival.
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  • New Real Time Location Sensing System Using Direction of Arrival Based Multilateration Technique

Abstract Views: 151  |  PDF Views: 4

Authors

Swetha Maran
Department of Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India
R. Jahnavi
Department of Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India
K. Gunaseelan
Department of Electronics and Communication Engineering, College of Engineering Guindy, Anna University, Chennai, India

Abstract


Real Time Location Sensing (RTLS) for indoor location estimation is an emerging technology. The challenging issues of this technology are finding the exact coordinates of the object with less number of RFID (Radio Frequency Identification) tags and also solving the over-deterministic equations. The existing techniques such as ML (Maximum Likelihood), ESPRIT (Estimated Signal Parameters via Rotational Invariance) find only the DOA (Direction of Arrival) of the signal and they apply only to special structure arrays. The existing localisation techniques such as triangulation, trilateration can solve the equations non linearly and hence have high degree of computational complextiy. To solve this problem, a new DOA based multilateration localisation technique have been proposed and their performances are analysed. In this approach, the position of the stationary object is determined by using Music based DOA and the localisation technique called MULTILATERATION. In this proposed DoA based multilateration technique, the nonlinear equations have been solved linearly which decreases the complexity of the proposed technique than the existing algorithms.  Since, the reference tags are placed only in the desired direction using DoA estimation, the number of reference tags required for the accurate estimation of location is significantly reduced than the existing techniques.


Keywords


Degree of Solvability, Direction of Arrival, Multilateration, Multiple Signal Classification, Real Time Location Sensing, Signal to Noise Ratio, Spatial Spectrum, Time Difference of Arrival.