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The direct measurement of distance-dependent information between wireless units represents a challenge for wireless locating systems, because it requires the exact time synchronization of separate wireless units. To avoid these synchronization efforts, many wireless locating systems only evaluate phase difference of arrival (PDOA) measurements. While simple PDOA localization techniques rely on multiangulation, advanced PDOA concepts like the holographic extended Kalman filter (HEKF) directly evaluate the measured phases without non-linear preprocessing. However, these differential phase measurement approaches are less sensitive than systems that can measure absolute phase variations, which allow the tracking of much smaller position changes than the signal’s carrier wavelength. This paper proposes to extend the HEKF by the evaluation of absolute phases in an incoherent measurement setup, which consists of a continuous wave (CW) beacon and several receivers. The developed quasi-coherent holographic extended Kalman filter (QCHEKF) uses the overdetermined PDOA measurements to estimate the phase–frequency relation between each beacon–receiver pair. Then, the established phase–frequency relations allow the evaluation of absolute phase measurements and, thus, the accurate localization and tracking of a simple, unsynchronized, narrowband CW beacon, even under severe multipath conditions. This novel concept is experimentally validated via 3D localization results in a challenging indoor scenario using a 24 GHz CW measurement setup. Here, the QCHEKF improves the achieved localization accuracy in comparison to the HEKF by 35 % from 0.78 cm to 0.51 cm, while the maximum deviation from the trajectory reduces by 68 % from 5 cm to 1.6 cm. Furthermore, the QCHEKF enables the exact tracking of fast changes in direction, which is usually a significant challenge for standard wireless target tracking systems.

In wireless sensor networks, spatially distributed nodes provide location-dependent sensor information. Therefore, knowledge about the 3D position of all nodes is crucial for the numerous applications that require autonomous mobility. Furthermore, to acquire the nodes' poses and the complete 6D network constellation, the 3D orientation of each node is also required. While many theoretical localization concepts exist for wireless sensor networks, there is still a lack of reliable system and localization concepts which enable robust real-time tracking in real-world scenarios. Therefore, we present a system approach based on an advanced 24 GHz wireless local positioning system, providing distance and angle measurements between pairs of nodes. Furthermore, an extended Kalman filter based localization algorithm is proposed, which evaluates these measurements to track the time varying 6D poses of all nodes in the network. Because only relative measurements are available, one node is chosen to define a joint navigation system. Hence, the proposed system works without any previously installed infrastructure or prior information of the network. The system and localization algorithm are validated by measurements performed in a mobile wireless sensor network comprising six nodes in an indoor scenario with strong multipath propagation. However, despite the challenging environment, the system allows for a stable and accurate 6D pose estimation of all robots in the network with 3D positioning root mean square errors of 6 to 15cm.

Massive multiple-input multiple-output (MIMO) techniques are being considered for the fifth generation (5G) mobile communication systems in order to deliver high multiplexing gain. However, hardware impairments like quadrature imbalance in mixers violate the requirement for channel reciprocity and may change, e.g., with temperature or while aging. In addition, advanced wireless localization techniques and the generation of predefined beam patterns require knowledge about all antenna phase center positions and the time and phase delay of all transmit and receive channels. Thus, an efficient online compensation method is needed that scales well for very large numbers of transceiver modules. We propose to extend the transmitter with a small measurement feature at the transmitter output based on one uncalibrated power detector per module as well as a single, external four-element backscatter array for the entire matrix. These enhancements facilitate a fast and efficient iterative calibration, which recognizes and mitigates all major error sources. Beside optimal communication throughput and energy efficiency, it thereby brings localization capabilities to mobile networks as an additional major benefit. For verification, a system of multiple cost-efficient 5.8-GHz massive MIMO transceivers with 150-MHz bandwidth and a backscatter array has been implemented. Measurement results demonstrate the capability of the proposed concept to efficiently compensate major error sources as well as its robustness.

Massive multiple-input multiple-output (MIMO) communication has gained huge attention throughout the last years as a key technology for fifth generation mobile communication systems, because they enable wide area coverage along with ultra-high data rates and low bit energy. Furthermore, for a high number of antennas, communication theory predicts nearly optimal performance using basic linear detection and precoding schemes. However, realizing such large-scale arrays (say 100 elements or more) is non-trivial and costly and hence, only few of them are available for public research. Most often, existing solutions are limited to the current mobile communication standards. We therefore propose the design and implementation of a low-cost ultra-versatile 120-antenna massive MIMO testbed applicable both in communication and localization research. An instantaneous bandwidth of 150 MHz at a center frequency of 5.8 GHz is covered. An indoor verification measurement with 24 parallel transmissions and a bandwidth of 125 MHz achieved a sum-rate of 22.8 Gb/s with only 1.02 % bit error rate resulting in an outstanding equivalent error-free spectral efficiency of 167.2 bit/s/Hz.