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where x ̂ is an estimate of the target node position x given by a positioning algorithm.
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By using a positioning algorithm to determine the optimal position, for the sinks, possibly even better performances can be obtained.
This paper proposed a positioning algorithm by combining vehicle Global Navigation Satellite System (GNSS) and mobile RFID readers.
In this study, a positioning algorithm which is inspired by model matching type positioning systems is presented for swarm robotics.
To do this, a positioning algorithm has been designed based on the Innovation-based Adaptive Estimation Kalman Filter (IAE_KF) by integrating the positioning measurements with vehicle kinematic information.
This information can be exploited by a weighted positioning algorithm in order to improve the accuracy of the position estimate.
After being processed by the positioning algorithm that is running on the fixed infrastructure, the locating result is sent back to the requester (the mobile to be located). .
After being processed by the positioning algorithm that is running on the fixed infrastructure, the locating result is sent back to the requester (the mobile to be located).
Thereby, a novel positioning algorithm based on mobile BS is proposed by utilizing two multipath signals.
We conducted a ten positioning algorithm test.
This article proposes an improved traditional positioning algorithm by using scatter constraint information.
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