An integrated positioning system for the Toronto Transit System

In this thesis, a hybrid positioning system is developed, which combines GPS, Dead Reckoning (DR) and Signpost technologies for the purpose of improving the Toronto Transit System bus service. The DR system is used as the main positioning system, while GPS and Signpost systems are used as aiding systems to compensate for the DR errors. The integration is done in the position domain, which simplifies the system design. A centralized Kalman filter with five states is developed to combine all the available measurements. Field tests have been designed and conducted to assess the system design and performance under various environmental conditions. It is shown that the achieved positioning accuracy of the integrated DR/GPS/Signpost system is at the few metres level in unobstructed environments. In addition, despite the signal obstruction in the downtown area, the positioning solution of the integrated system is still sufficiently precise.

An integrated positioning system for the Toronto Transit System

In this thesis, a hybrid positioning system is developed, which combines GPS, Dead Reckoning (DR) and Signpost technologies for the purpose of improving the Toronto Transit System bus service. The DR system is used as the main positioning system, while GPS and Signpost systems are used as aiding systems to compensate for the DR errors. The integration is done in the position domain, which simplifies the system design. A centralized Kalman filter with five states is developed to combine all the available measurements. Field tests have been designed and conducted to assess the system design and performance under various environmental conditions. It is shown that the achieved positioning accuracy of the integrated DR/GPS/Signpost system is at the few metres level in unobstructed environments. In addition, despite the signal obstruction in the downtown area, the positioning solution of the integrated system is still sufficiently precise.

Design and Development of GPS Navigation and Positioning System based on AutoCAD Platform

According to the design of the software system, the positioning chip configured in the positioning terminal can be GPS, or a hybrid positioning system, plus optional position differential function, which ensures the positioning accuracy and maintains data security at the same time. Software system using cloud computing technology and C/S, B/S hybrid architecture for development, the system can be deployed on an ordinary PC to achieve greater capacity and higher performance, companies or individuals only need to be equipped with positioning terminals can directly use the system, but also according to their own needs to further modify the system realized in this paper customized. This greatly reduces the development and maintenance costs of the system and is beneficial to the promotion and use of the system. The satellite positioning information is received from the positioning terminal, decoded according to the present decoding algorithm, and sent to the database server for storage; remote control commands are received from the terminal administrator, processed, and sent to the positioning terminal. Web server, which provides access service to the user's operation platform. Service server, which provides service support for business logic to the user operation platform. The user operation platform is divided into the ordinary user operation platform and the terminal administrator operation platform.

Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

The fifth generation (5G) cellular communication system is designed to support Time Difference of Arrival (TDOA), Round-Trip Time (RTT), and Direction of Arrival (DOA) measurements for indoor positioning. To mitigate the positioning error caused by non-line-of-sight (NLOS), existing base station selection methods identify channel conditions and only use line-of-sight (LOS) signals for positioning. However, different selected base station combination would lead to a different geometric dilution of precision (GDOP), base station selection based only on channel condition is not fully applicable for the hybrid positioning. This paper derives the GDOP for the hybrid TDOA, RTT, and DOA positioning, and proposes a GDOP-assisted base station selection method, which is based on both channel conditions and GDOP value changes. The simulation shows that using the proposed base station selection method could lead to higher positioning accuracy than base station selection based only on channel condition. In the simulation, in the side region of the scenario, where the change of selected base station combination causes a notable increment in GDOP value, the positioning accuracy improvement caused by the proposed method is greater than that in the center region.

Recurrent Neural Network-Based Hybrid Localization for Worker Tracking in an Offshore Environment

Accidents involving marine crew members and passengers are still an issue that must be studied and obviated. Preventing such accidents at sea can improve the quality of life on board by ensuring a safe ship environment. This paper proposes a hybrid indoor positioning method, an approach which is becoming common on land, to enhance maritime safety. Specifically, a recurrent neural network (RNN)-based hybrid localization system (RHLS) that provides accurate and efficient user-tracking results is proposed. RHLS performs hybrid positioning by receiving wireless signals, such as Wi-Fi and Bluetooth, as well as inertial measurement unit data from smartphones. It utilizes the RNN to solve the problem of tracking accuracy reduction that may occur when using data collected from various sensors at various times. The results of experiments conducted in an offshore environment confirm that RHLS provides accurate and efficient tracking results. The scalability of RHLS provides managers with more intuitive monitoring of assets and crews, and, by providing information such as the location of safety equipment to the crew, it promotes welfare and safety.

Hybrid Positioning for Smart Spaces: Proposal and Evaluation

Positioning capabilities have become essential in context-aware user services, which make easier daily activities and let the emergence of new business models in the trendy area of smart cities. Thanks to wireless connection capabilities of smart mobile devices and the proliferation of wireless attachment points in buildings, several positioning systems have appeared in the last years to provide indoor positioning and complement GPS for outdoors. Wi-Fi fingerprinting is one of the most remarkable approaches, although ongoing smart deployments in the area of smart cities can offer extra possibilities to exploit hybrid schemes, in which the final location takes into account different positioning sources. In this paper we propose a positioning system that leverages common infrastructure and services already present in smart spaces to enhance indoor positioning. Thus, GPS and WiFi are complemented with access control services (i.e., ID card) or Bluetooth Low Energy beaconing, to determine the user location within a smart space. Better position estimations can be calculated by hybridizing the positioning information coming from different technologies, and a handover mechanism between technologies or algorithms is used exploiting semantic information saved in fingerprints. The solution implemented is highly optimized by reducing tedious computation, by means of opportunistic selection of fingerprints and floor change detection, and a battery saving subsystem reduces power consumption by disabling non-needed technologies. The proposal has been showcased over a smart campus deployment to check its real operation and assess the positioning accuracy, experiencing the noticeable advantage of integrating technologies usually available in smart spaces and reaching an average real error of 4.62 m.