Abstract
For many commercial applications it is of interest to identify and localize objects. The most traditional way of identifying objects is to use labels with a printed barcode, an alternative can be UHF RFID tags.
This thesis describes possible solutions to the localization problem. By measuring the phase difference between the transmitted continuous wave and the received backscatter at different frequencies, it is possible to estimate the distance. By measuring the distance to three readers it is possible to determine the location of a tag with the help of trilateration. To overcome the influence of the environment on the distance estimate, this thesis suggests the use of reference tags and the K-Nearest Neighbors (KNN) algorithm to derive a location. The results in terms of average localization error are similar to a RSSI based method, about 0.4 m.
Another approach is to use an array of multiple antennas, a so-called phased array. When a signal is received by two different antennas there will be a time delay between the signals dependent on the Direction of Arrival (DOA) of the signal. For an array with more antennas the MUSIC or EPSRIT algorithm can be used. The observation that a tag is within the near field of a phased array leads to the fact that there is an extra phase difference depending on the distance of the tag to the array. An average angle error of 3 to 4 degrees and a range error in the order of 0.3 m is measured. Differences with measurements in an anechoic room show that the performance of the system heavily depends on the environment.
To decrease the energy consumption of a multi-array system, this thesis explores the use of heavily quantized signals instead of the high resolution signals used in the near field experiments. The DOA estimation algorithms are based on correlations between the different array channels. By using single bit quantized signals, errors are introduced in these correlations, which can be corrected. Experiments in a realistic environment show that by using single-bit quantized signals, the DOA estimation degrades from 4 to 6 degrees.
This thesis describes possible solutions to the localization problem. By measuring the phase difference between the transmitted continuous wave and the received backscatter at different frequencies, it is possible to estimate the distance. By measuring the distance to three readers it is possible to determine the location of a tag with the help of trilateration. To overcome the influence of the environment on the distance estimate, this thesis suggests the use of reference tags and the K-Nearest Neighbors (KNN) algorithm to derive a location. The results in terms of average localization error are similar to a RSSI based method, about 0.4 m.
Another approach is to use an array of multiple antennas, a so-called phased array. When a signal is received by two different antennas there will be a time delay between the signals dependent on the Direction of Arrival (DOA) of the signal. For an array with more antennas the MUSIC or EPSRIT algorithm can be used. The observation that a tag is within the near field of a phased array leads to the fact that there is an extra phase difference depending on the distance of the tag to the array. An average angle error of 3 to 4 degrees and a range error in the order of 0.3 m is measured. Differences with measurements in an anechoic room show that the performance of the system heavily depends on the environment.
To decrease the energy consumption of a multi-array system, this thesis explores the use of heavily quantized signals instead of the high resolution signals used in the near field experiments. The DOA estimation algorithms are based on correlations between the different array channels. By using single bit quantized signals, errors are introduced in these correlations, which can be corrected. Experiments in a realistic environment show that by using single-bit quantized signals, the DOA estimation degrades from 4 to 6 degrees.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 30 Jun 2017 |
| Place of Publication | Enschede |
| Publisher | |
| Print ISBNs | 978-90-365-4250-0 |
| DOIs | |
| Publication status | Published - 30 Jun 2017 |