Real-Time Relative Positioning System Implementation Employing Signals of Opportunity, Inertial, and Optical Flow Modalities


Current navigation technologies are relying on global navigation satellite system (GNSS) information. As in terms of reliability and precision next-generation autonomous vehicle requirements cannot be fully satisfied by GNSS, a sensor information fusion must be employed, leading to the exploration of new positioning methods. In this work, a reliable relative positioning solution in GNSS-challenged areas is investigated, using a combination of signals of opportunity (SOPs), inertial, and optical flow data. The proposed real-time relative positioning system exploits the fused data in the absence of GNSS signals for localization, employing a tracking algorithm to estimate the agent’s trajectory in space and time. Extensive outdoor experiments employing an Unmanned Aerial Vehicle (UAV) are carried out to demonstrate the applicability of the proposed technique, validating its performance against various positioning approaches, including GNSS.


Vehicular technology is developing rapidly in order to achieve higher levels of automation. A navigation system that is reliable and accurate is an absolute need for the implementation of autonomous vehicle technology and the development of intelligent transportation infrastructure. GNSS positioning, even though the main localization technology utilized nowadays, can in some instances suffer from interference, jamming, or spoofing attacks, or it can even become unavailable at certain locations. Various localization solutions, such as the utilization of inertial navigation systems (INS), and various sensors (e.g., light, and range sensors) have been proposed to localize a vehicle in GNSS-challenged areas. A number of issues with the aforementioned solutions, such as degradation of data and signal loss due to multipath and antenna obstruction, have resulted in the further exploration of alternative localization methods. An indicative taxonomy of such techniques, including the proposed system (optical flow-relative positioning system – OF-RPS), is presented in the figure below.

Apart from the aforementioned localization techniques, SOPs (e.g., AM/FM radio, cellular, TV signals, etc.) can also be utilized for location estimation, since they are freely available and are usually transmitted at high powers. A number of works in the literature have investigated SOPs for positioning purposes, mainly assuming that a priori knowledge of the receiver’s reference position and the transmitter’s location is available.

Fig. 1: - Broad classification of positioning techniques.
Broad classification of positioning techniques.

This work complements these studies, extending our previous work, as it introduces a real-time relative positioning system, utilizing fused information without the use of any GNSS information. Specifically, the main contributions include:

  • A novel real-time relative positioning system (denoted as OF-RPS) that localizes the agent by fusing SOP information with inertial and optical flow measurements, requiring no information about the transmitters’ location or any GNSS signal information. An extended Kalman filter (EKF) solution is utilized to improve the localization performance and a frequency selection algorithm (FSA) is employed to reduce the processing time requirements.
  • A prototype implementation of the proposed solution, including extensive testing in a real-world outdoor environment to demonstrate the feasibility of the developed framework. Experimental results assess and validate its performance thoroughly, and indeed show that relative positioning can be achieved using only the fused information and without the use of any GNSS data.

The structure of this paper is as follows. Related work is included in Section II, and the description of the methodology employed is described in Section IIISection IV elaborates on the system’s framework, while experimental results are illustrated in Section V. Finally, concluding remarks are presented in Section VI.

IEEE Publication