RFID Indoor Tracking based on Inter-tags Distance Measurement
ABSTRACT Summary form only given. Indoor tracking and localization is a crucial ingredient in many ubiquitous computing applications and robotics. In many applications there is the need to know the location of the objects. While in the near future everything will be tagged with radio frequency identification (RFID) tags, the localization of these tags in their environment is becoming an important feature for the RFID based ubiquitous computing applications. Due to its lower cost and its technical capabilities, RFID tagged object tracking can have a wide diverse variety of applications including scientific, military, and public safety. In this paper we propose a tracking algorithm for objects attached by UHF RFID tags by means of two RFID antennas and landmarks to reduce the localization cost and environment complexity. This algorithm uses RFID map made from passive or active references tags with known location (landmarks) to locate any unknown tag detected by the RFID reader antennas. It measures the distances between the readers and the common detected tags using the large scale path loss propagation model, and calculates the distance between the unknown tag and all the detected landmarks (inter-tags distance). With the multilateration technique the system is able to estimate the position of the unknown tag. The location estimation of the target will be independent to the reader's position. The research challenge corresponds to achieve an accurate indoor tracking system using two mobile RFID readers taking in consideration the limitation of RFID technology. This tracking algorithm is based on received signal strength (RSS) measurement to measure the reader-tags distance and target-landmarks distance to estimate the target location. To minimize the effect of the RSS and the process measurement noises on the position estimation, maximum likelihood estimator (MLE), map matching and Kalman filter are applied. Here, we investigate the use of Kalman filter to improve the precisi-
on and RFID map matching to improve the accuracy. Results obtained after simulations demonstrate the validity and suitability of the proposed algorithm to provide high performance level in terms of accuracy and scalability.
- SourceAvailable from: J. Alex Thomasson
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- "All compatible tags within the reader's range are activated by the signal and respond by sending out stored data. Bekkali and Matsumoto (2007) created a tracking algorithm that calculated the distance and position of robots relative to stationary RFID antennas. Since they are stationary while a cotton module is being built, module builders could be set up as RFID antenna (reader) locations, and RFID tags could then be attached to the harvesters and boll buggies. "
ABSTRACT: The ability to map profit across a cotton field would enable producers to determine where money is being made or lost on their farms and to implement precise field management practices to facilitate the highest return possible on each portion of a field. Mapping profit requires knowledge of site-specific costs and revenues, including yield and price. Price varies site-specifically because fiber quality varies, so mapping fiber quality is an important component of profit mapping. To map fiber quality, the harvest location of individual cotton bales must be known, and thus a system to track the harvest location of cotton modules must be available. To this end, a wireless module-tracking system was recently developed, but automation of the system is required before it will find practical use on the farm. In Part 1 of this report, research to develop automatic triggering of wireless messages is described. In Part 2, research to enable the system to function with multiple harvesting machines of the same type in the same field – a common situation in commercial cotton farming – is described along with testing of the entire automated wireless module-tracking system (WMTS). An RFID system was incorporated, and it enabled the WMTS to correctly and consistently differentiate among various harvesting vehicles. The improved WMTS subsequently sent wireless messages to the correct machines when cotton transfers were made in the presence of multiple harvest machines. Overall testing proved that the automated WMTS worked largely as designed. When both complete and partial cotton basket dumps were simulated, the correct wireless-messaging decision was made 100% of the time.Graphical abstractResearch highlights▶ RFID used in wireless module tracking to distinguish among cotton harvest machines. ▶ Automated wireless module tracking sent wireless messages to the correct machine. ▶ Wireless module tracking with sensor-based automation and RFID worked as designed.Computers and Electronics in Agriculture 01/2011; 75(1):34-43. DOI:10.1016/j.compag.2010.09.015 · 1.49 Impact Factor
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ABSTRACT: This paper aims to locate the target position by using RFID Readers and tags with minimum error. After investigating the existing fingerprinting location technique, we find that the distribution of RSSI-value at each sample point is fluctuant even in the same position. Therefore, we propose an enhanced algorithm to the existing deterministic algorithms. The proposed enhancement approach collects ranges of possible RSSI-values from either sample point or target object to build the probability model, which is different from original algorithm that only saves one single RSSI-value at each point into a database, then several sets of RSSI-values are got for further location by using permutation and combination. Unlike the existing techniques, more than one locations are computed and the final location is the weighted average of those computed locations. simulation results and experimental comparisons are shown, in order to prove the accuracy of location estimation is improved.