The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75 th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.

This paper presents a FLIR/INS/RA integrated landing guidance method to provide information of aircraft states and carrier dynamics for fixed-wing aircraft landing on the aircraft carrier in low-visibility weather and high sea states. The method utilizes the Forward-Looking Infrared (FLIR) system, the Inertial Navigation System (INS), and the Radio Altimeter (RA) as sensors, to track infrared cooperated targets on the aircraft carrier. Several algorithms like the Newton iterative algorithm, the Kalman Filter (KF), and the Wavelet Transform (WT) are employed to compute real-time and high-precision estimates of the aircraft states (runway-related position, attitude, and velocity) and the carrier dynamics (pitch, roll, and heave). A simulation experiment is conducted and shows satisfactory results for the aircraft carrier landing guidance.

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In this article, we describe a visual/inertial integrated carrier landing guidance algorithm for aircraft carrier landing operations. The airborne vision system and the inertial navigation system are employed as sensors to obtain feature points of carrier runway as well as the aircraft inertial measurements. In this algorithm, visual and inertial information are integrated, and the Pose from Orthographic Projection and Scaling with Iterations algorithm is utilized to estimate aircraft position and carrier motion. A simulation was constructed validating this algorithm, and the results of this simulation show satisfactory accuracy as well as high efficiency in carrier landing guidance.

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