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Indoor localization based on UWB technology
Bauer, Jan Jiří ; Vyroubal, Petr (referee) ; Čech, Ondřej (advisor)
This bachelor thesis is exploring ways to localize an object in space, primarily using UWB technology. Diverse ways to determine distance (TWR, RSSI, TDoA), location in space (triangulation, multilateration, particle filter), and filters (LSM, Kalmann filter) are explained. Using development board ESP-32 UWP Pro localization system is realized, using TWR and particle filter. This system was calibrated and tested in a real environment.
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Wireless Localization Module with Low-Power Firmware Based on RTOS
Lipka, Radim ; Bardonek, Petr (referee) ; Šimek, Václav (advisor)
This thesis focuses on the design and implementation of the wireless localization module, using UWB technology with emphases on low-power firmwre based on RTOS. Wireless localization is based on TDoA algorithm. The resulting HW module is designed as a four layer PCB, based on MCU crf52832 (ARM Cortex M4) and UWB module DevaWave DW1000. Firmware is implemented using FreeRTOS with emphasis on low power consumption. For hardware implementation, Eagle CAD was used. Firmware is implemented in C and Assembly programming languages.
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Packet Analyser for UWB based on 15.4a standard
Leixner, Martin ; Šimek, Milan (referee) ; Mráz, Ľubomír (advisor)
The aim of this work is study the standard for wireless sensor networks IEEE 802.15.4a. Design and implementation of a packet analyzer for ultra wideband technology com- pliant with IEEE 802.15.4a standard. Integrate packet analyzer to inspection software Wireshark and implement dissector for view packets. Finally, analyze and evaluate the parameters of the proposed packet analyzer.
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Classification of Direct and Reflected Signal Using Embedded System
Chalko, Miroslav ; Strnadel, Josef (referee) ; Šimek, Václav (advisor)
This thesis aims to design and implement an algorithm for classification of signals that are used for tracking objects using ultra-wideband technology. The classification method should be able to detect an obstruction between receiver and transmitter, which means to classify signals as those with line of sight (LOS) and non-line of sight (NLOS). This system must be quick and lightweight enough, so real-time detection can be achieved directly in the embedded system. While searching for the solution, multiple classification methods were examined. The best-performing ones involved numerous variants of decision tree classifiers. Considering the restricted computing power of embedded devices, random forest classifier was chosen as the final solution. This classification method was able to achieve accuracy of up to 89% while evaluating the dataset. When deployed in real-life environment, it was able to detect an object between transmitter and receiver. Classification and calculation of parameters takes 6000 instruction cycles and the algorithm fits into 4kB of memory. Results of this thesis enable improvement of existing solutions for detection of NLOS signals that degrade tracking performance. This will boost the accuracy of localization while tracking objects in indoor environments.
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Classification of Direct and Reflected Signal Using Embedded System
Chalko, Miroslav ; Strnadel, Josef (referee) ; Šimek, Václav (advisor)
This thesis aims to design and implement an algorithm for classification of signals that are used for tracking objects using ultra-wideband technology. The classification method should be able to detect an obstruction between receiver and transmitter, which means to classify signals as those with line of sight (LOS) and non-line of sight (NLOS). This system must be quick and lightweight enough, so real-time detection can be achieved directly in the embedded system. While searching for the solution, multiple classification methods were examined. The best-performing ones involved numerous variants of decision tree classifiers. Considering the restricted computing power of embedded devices, random forest classifier was chosen as the final solution. This classification method was able to achieve accuracy of up to 89% while evaluating the dataset. When deployed in real-life environment, it was able to detect an object between transmitter and receiver. Classification and calculation of parameters takes 6000 instruction cycles and the algorithm fits into 4kB of memory. Results of this thesis enable improvement of existing solutions for detection of NLOS signals that degrade tracking performance. This will boost the accuracy of localization while tracking objects in indoor environments.
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Wireless Localization Module with Low-Power Firmware Based on RTOS
Lipka, Radim ; Bardonek, Petr (referee) ; Šimek, Václav (advisor)
This thesis focuses on the design and implementation of the wireless localization module, using UWB technology with emphases on low-power firmwre based on RTOS. Wireless localization is based on TDoA algorithm. The resulting HW module is designed as a four layer PCB, based on MCU crf52832 (ARM Cortex M4) and UWB module DevaWave DW1000. Firmware is implemented using FreeRTOS with emphasis on low power consumption. For hardware implementation, Eagle CAD was used. Firmware is implemented in C and Assembly programming languages.
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Packet Analyser for UWB based on 15.4a standard
Leixner, Martin ; Šimek, Milan (referee) ; Mráz, Ľubomír (advisor)
The aim of this work is study the standard for wireless sensor networks IEEE 802.15.4a. Design and implementation of a packet analyzer for ultra wideband technology com- pliant with IEEE 802.15.4a standard. Integrate packet analyzer to inspection software Wireshark and implement dissector for view packets. Finally, analyze and evaluate the parameters of the proposed packet analyzer.
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