Abstract
This paper presents an approach to analyse the quality, in terms of precision and reliability, of a system which integrates—at the observation-level—landmark positions and GNSS measurements, obtained with a single camera and a digital map, and a single frequency GNSS receiver respectively. We illustrate the analysis by means of design computations, and we present the actual performance by means of a small experiment in practice. It is shown that the integration model is able to produce a position solution even when both sensors individually fail to do so. With realistic assumptions on measurement noise, the proposed integrated, low-cost system can deliver a horizontal position with a precision of better than half a meter. The external reliability of the integrated system is at the few decimetre-level, showing that the impact of undetected faults in the measurements, for instance incorrectly identified landmarks in the image, on the horizontal position is limited and acceptable, thereby confirming the fault-robustness of the system.
Highlights
The integration aims to combine the output from the two sensors, the low-cost Global NavigationSatellite System (GNSS) receiver for SF-Precise Point Positioning (PPP) and the monocular camera
When only pseudorange observations of the 5 highest elevation satellites are used, the Z0 degrades significantly, since the selection reduces the variation in vertical direction, and it increases the difficulty for GNSS to estimate Z0 together with the receiver clock bias
When pre-surveyed landmark positions are accurate at the 20-cm-level, the integration model is able to estimate the horizontal position coordinates X0, Y0 within a standard deviation of about 0.5 m, and the vertical position coordinate Z0 and the antenna-camera offset t0 within about 1.5 m, and heading κ within 0.1 degree, with fair correlation between the unknowns, except between Z0, t0 and GNSS receiver clock bias tr
Summary
The goal of this study is to develop a tightly coupled integration model of Global NavigationSatellite System (GNSS) and monocular vision (single camera) measurements, and to propose a method to analyse the positioning performance in particular in terms of precision and reliability, for instance for the application of advanced car navigation and further levels of automation of road-vehicles, such as assisted driving—this paper is largely based on the research in [1].We will use single frequency Precise Point Positioning (PPP) GNSS, and a single camera together with a High Definition (HD) map [2] to observe well identifiable objects, which we will call landmarks.These two sensors are complementary, as the camera relies on the availability of landmarks around the vehicle, which is typically large in urban areas, and low in rural areas, and GNSS performs generally well in the latter.Precise Point Positioning (PPP) is a positioning technique which utilizes un-differenced pseudorange and carrier phase measurements with the aid of GNSS data products from a global network of reference stations providing precise satellite orbits and clocks [3,4,5]. We will use single frequency Precise Point Positioning (PPP) GNSS, and a single camera together with a High Definition (HD) map [2] to observe well identifiable objects, which we will call landmarks. These two sensors are complementary, as the camera relies on the availability of landmarks around the vehicle, which is typically large in urban areas, and low in rural areas, and GNSS performs generally well in the latter. This technique has been applied for lane level positioning [7,8]
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