No abstract

Many satellite systems require knowledge about inter-satellite distances. Inter-satellite links provide direct connectivity between satellites and may be used for ranging, while they remove the need of dedicated hardware. This paper addresses inter-satellite ranging at the Low Earth Orbit (LEO) using S-Band signals. We take the requirements from recent missions and future applications into account and analyze the factors that limit ranging. We show how these factors affect the quality of distance estimation in terms of the Cramér-Rao Lower Bound for ranging. Two-way-ranging (TWR) provides the best accuracy and sustains the low-cost objective of small satellites. We further propose an enhanced TWR message exchange that enables on-the-fly delay calibration and sub-sample corrections. We implemented the transceiver modules on a Software-Defined Radio (SDR) platform and evaluated them with real-world data. The results show that the proposed ranging algorithm achieves an accuracy of few centimeters

Driven by an ever-increasing demand for higher data rates, 5G introduced communication over the millimeterwave (mmWave) bands to fulfill this requirement. High data transmissions in this spectrum are enabled by beamforming massive MIMO antennas and the available allocated bandwidth. Of interest is the utilization of mmWave for high-accuracy positioning applications, motivated by the allocated bandwidth and beamforming characteristics of such systems. This paper provides numerical simulations on the 5G positioning reference signal reception and shows, for a real-world indoor environment, positioning performance results. The accuracy of ToA-based positioning in dependence of the beam shape and direction is determined to be at least within 6 cm for LOS scenarios. We also investigate the impact of LOS path obstructions on the performance. Achieving centimeter level accuracy is subject to improvements through continuing research and refinements.

In this paper we study the problem of estimating the unknown delay(s) in a system where we receive a linear combination of several delayed copies of a known transmitted waveform. This problem arises in many applications such as timing-based localization or wireless synchronization. Since accurate delay estimation requires wideband signals, traditional systems need high-speed AD converters which poses a significant burden on the hardware implementation. Compressive sensing (CS) based system architectures that take measurements at rates significantly below the Nyquist rate and yet achieve accurate delay estimation have been proposed with the goal to alleviate the hardware complexity. In this paper, we particularly discuss the design of the measurement kernels based on a frequency-domain representation and show numerically that an optimized choice can outperform randomly chosen functionals in terms of the delay estimation accuracy

Nowadays, many tracking systems in football provide positional data of players but only a few systems provide reliable data of the ball itself. The tracking quality of many available systems suffers from high ball velocities of up to 34 ms-1 and from the occlusion of both the players and the ball. Knowledge about the position and velocity of the football can yield valuable information for players, coaches and the media. To assess the accuracy of the football's velocity provided by the radio-based tracking system RedFIR, we used a ball shooting machine to repeatedly simulate realistic situations at different velocities ranging from 7.9 ms-1 to 22.3 ms-1 in an indoor environment. We then compared velocity estimates for 50 shots at five speed levels with ground truth values derived from light gates by way of mean percentage error (MPE) and Bland-Altman analysis. The speed values had an MPE of 2.6% (-0.49 ms-1)