Vector tracking loop design for GPS receivers

Download

index.pdf

Date

2016

Author

Üzel, Deniz

Metadata

Show full item record

Item Usage Stats

393
views

334
downloads

This study describes the design of a modern GPS receiver architecture based on vector tracking loops. Since the traditional tracking loops process the signals independently, there is no information exchange between channels. Due to that fact, aiding of weaker signals in the presence of relatively strong signals is impossible. On the other hand, vector tracking loops simultaneously process the signals from all visible channels. Therefore, they are able to perform better than the traditional tracking loops in degraded signal environments where carrier to noise ratio is significantly low. In this thesis, a review of GPS receivers and satellite constellation is firstly presented. Then, the implementation details of traditional tracking loops and Vector Delay/Frequency Lock Loop (VDFLL) algorithm, which is a common type of the vector tracking architectures, are discussed. In addition, a modified version of VDFLL, which has a navigation filter with less number of states, is proposed. The mentioned algorithms are implemented in MATLAB environment. The performances of these algorithms are compared by using a Spirent GPS signal simulator. These performance comparison results indicate that the vector tracking algorithms have improved signal tracking capabilities in low carrier to noise ratio environments. Besides the superiority of the vector tracking algorithms, it is also shown that the modified version of VDFLL algorithm may be an alternative to original VDFLL with the advantage of lower computational load and almost similar performance in degraded signal environments. These algorithms can be used to track GPS signals in challenging GPS signal environments such as urban canyons and indoor areas.

Subject Keywords

GPS receivers., Kalman filtering., Tracking (Engineering)., Global Positioning System.

URI

http://etd.lib.metu.edu.tr/upload/12619787/index.pdf
https://hdl.handle.net/11511/25468

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

GPS-Based Real-Time Orbit Determination of Low Earth Orbit Satellites Using Robust Unscented Kalman Filter Karslıoğlu, Mahmut Onur; Erdogan, Eren; Pamuk, Onur (2017-11-01) In this research, a novel algorithm for real-time orbit determination (RTOD) is presented using the robust unscented Kalman filter (RUKF) with global positioning system (GPS) group and phase ionospheric correction (GRAPHIC) observables. To increase the reliability of the solution, a robust approach is included in the UKF to cope with the bad, invalid, or degraded measurements leading to the divergence or inaccurate output of the filter. Robustness is provided by making the filter less sensitive to faulty me...
Sensor Fusion of a Camera and 2D LIDAR for Lane Detection Schmidt, Klaus Verner (null; 2019-04-26) This paper presents a novel lane detection algorithm based on fusion of camera and 2D LIDAR data. On the one hand, objects on the road are detected via 2D LIDAR. On the other hand, binary bird’s eye view (BEV) images are acquired from the camera data and the locations of objects detected by LIDAR are estimated on the BEV image. In order to remove the noise generated by objects on the BEV, a modified BEV image is obtained, where pixels occluded by the detected objects are turned into background pixels. Then,...
Improved positioning by distance-based differential GPS Ghaziani, Matin; Konukseven, Erhan İlhan; Koku, Ahmet Buğra; Department of Mechanical Engineering (2013) This study presents a new method of differential GPS which is based on distance between GPS receivers. To navigate a robot on unstructured area, different methods have been used. One of the important methods is using GPS. Using single GPS leads to inaccurate navigation of a robot. One way to overcome this problem is using Differential GPS which is based on using one or several based stations and rover receivers. These base stations depend on exact coordinate of its coordinates and without them; this method ...
Electromagnetic Target Classification using time frequency analysis and neural networks Sayan, Gönül; Leblebicioğlu, Mehmet Kemal (Wiley, 1999-04-01) This paper demonstrates the feasibility and advantages of using a self-organizing map (SOM)-type neural network classifier for electromagnetic target recognition. The classifier is supported by a novel feature extraction unit in which the Wigner distribution (WD), a time-frequency representation, is utilized for the extraction of natural-resonance-related energy feature vectors from scattered fields. The proposed target classification technique is tested for a set of canonical targets, displaying an excelle...
Radar target classification method with reduced aspect dependency and improved noise performance using multiple signal classification algorithm SEÇMEN, MUSTAFA; Sayan, Gönül (Institution of Engineering and Technology (IET), 2009-12-01) This study introduces a novel aspect and polarisation invariant radar target classification method based on the use of multiple signal classification (MUSIC) algorithm for feature extraction. In the suggested method, for each candidate target at each designated reference aspect, feature matrices called 'MUSIC spectrum matrices (MSMs)' are constructed using the target's scattered data at different late-time intervals. An individual MSM corresponds to a map of a target's natural resonance-related power distri...

Citation Formats

D. Üzel, “Vector tracking loop design for GPS receivers,” M.S. - Master of Science, Middle East Technical University, 2016.