Traditional satellite positioning systems have limited resolution and have proved inaccuratein areas such as urban canyons where signals are subject to bounce phenomena or indeed may be entirely unavailable. An alternative method of positioning is that of tri/multilateration, which uses known positions and distances from beacon points to locate a receiver. In this project, a software was developed which used DSRC Basic Safety Messages (containing locational information) in combination with Received Signal Strength metrics (translated to distance information) to carry out such positioning in static environments. Initial studies confirmed that a signal received on the Craton 2 hardware was subject to considerable signal strength spread approximating a Gaussian distribution. A software was developed to simulate BSMs, including a measure of perturbation, over TCP. Three different traffic scenarios were constructed. Furthermore, multilaterationsoftware was developed to receive the BSMs and calculate position using three separate algorithms. The performance of these algorithms in the three different traffic scenarios was then evaluated. Lastly, the multilateration software was further developed to allow for the capture and processing of real BSMs sent on the 5.9 GHzband. The multilateration software was capable of determining the location of the receiver to varying degrees of accuracy, depending on the geometrical distribution of surrounding vehicles and the algorithm used to multilaterate. The 3D Linear Least Squares method performed well in situations where beacons were well spaced in three dimensions. Other implemented multilateration algorithms, i.e., a 2D Linear Least Squares method and a 3D Gauss Newton method, performed better in typical traffic scenarios where vehicles tend to be coplanar.The software developed provides a useful starting point for further developmentof static, but also dynamic, multilateration algorithms.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-97682 |
Date | January 2020 |
Creators | Galbraith, Andrew |
Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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