Distributed and adaptive location identification system for mobile devices

Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments

Positioning in time and space: cost-effective exterior orientation for airborne archaeological photographs

Since manned, airborne aerial reconnaissance for archaeological purposes is often characterised by more-or-less random photographing of archaeological features on the Earth, the exact position and orientation of the camera during image acquisition becomes very important in an effective inventorying and interpretation workflow of these aerial photographs. Although the positioning is generally achieved by simultaneously logging the flight path or directly recording the camera's position with a GNSS receiver, this approach does not allow to record the necessary roll, pitch and yaw angles of the camera. The latter are essential elements for the complete exterior orientation of the camera, which allows – together with the inner orientation of the camera – to accurately define the portion of the Earth recorded in the photograph. This paper proposes a cost-effective, accurate and precise GNSS/IMU solution (image position: 2.5 m and orientation: 2°, both at 1σ) to record all essential exterior orientation parameters for the direct georeferencing of the images. After the introduction of the utilised hardware, this paper presents the developed software that allows recording and estimating these parameters. Furthermore, this direct georeferencing information can be embedded into the image's metadata. Subsequently, the first results of the estimation of the mounting calibration (i.e. the misalignment between the camera and GNSS/IMU coordinate frame) are provided. Furthermore, a comparison with a dedicated commercial photographic GNSS/IMU solution will prove the superiority of the introduced solution. Finally, an outlook on future tests and improvements finalises this article

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

AbstractAiming at mitigating multipath effect in dynamic global positioning system (GPS) satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square (RLS) algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators’ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase