This paper considers an estimator of the parameters in a linear-in-the-parameter signal, based on its binary quantization. It shows an analysis of the systematic errors for growing lengths of the data set. It also shows how to express the cost function, when the minimum is reached. Zero-mean additive noise is assumed in the model, having independent outcomes. Furthermore, a method is introduced to validate the estimation process. Monte Carlo results validate the proposed analyses.

This paper describes the design and realization of a Magnetic Indoor Positioning System. The system is entirely realized using off-the-shelf components and is based on inductive coupling between resonating coils. Both system-level architecture and realization details are described along with experimental results. The realized system exhibits a maximum positioning error of less than 10 cm in an indoor environment over a 3×3 m2 area. Extensive experiments in larger areas, in non-line-of-sight conditions, and in unfavorable geometric configurations, show sub-meter accuracy, thus validating the robustness of the system with respect to other existing solutions.

In this paper we present a hand tracking system based on magnetic positioning. A single magnetic node is mounted on each fingertip, and two magnetic nodes on the back side of the hand. A fixed array of receiving coils is used to detect the magnetic field, from which it is possible to infer position and orientation of each magnetic node. A kinematic model of the whole hand has been developed. Starting from the positioning data of each magnetic node, the kinematic model can be used to calculate position and flexion angle of each finger joint, plus the position and orientation of the hand in space. Relying on magnetic fields, the hand tracking system can work also in nonline-of-sight conditions. The gesture reconstruction is validated by comparing it with a commercial hand tracking system based on a depth camera. The system requires a small amount of electronics to be mounted on the hand. This would allow building a light and comfortable data glove that could be used for several purposes: human-machine interface, sign language recognition, diagnostics, and rehabilitation.

This paper describes the design and the realization of a low-frequency ac magnetic-field-based indoor positioning system (PS). The system operation is based on the principle of inductive coupling between wire loop antennas. Specifically, due to the characteristics of the ac artificially generated magnetic fields, the relation between the induced voltage and the distance is modeled with a linear behavior in a bilogarithmic scale when a configuration with coplanar, thus equally oriented, antennas is used. In this case, the distance between a transmitting antenna and a receiving one is estimated using measurements of the induced voltage in the latter. For a high operational range, the system makes use of resonant antennas tuned at the same nominal resonant frequency. The quality factors act as antenna gain increasing the amplitude of the induced voltage. The low-operating frequency is the key factor for improving robustness against nonline-of-sight (NLOS) conditions and environment influences with respect to other existing solutions. The realized prototype, which is implemented using off-the-shelf components, exhibits an average and maximum positioning error, respectively, lower than 0.3 and 0.9 m in an indoor environment over a large area of 15 m × 12 m in NLOS conditions. Similar performance is obtained in an outdoor environment over an area of 30 m × 14 m. Furthermore, the system does not require any type of synchronization between the nodes and can accommodate an arbitrary number of users without additional infrastructure.

In this paper, an ultrasonic positioning system is presented and characterized, based on the usage of a portable grid of beacons and of a few fixed anchors. Since the beacon grid can be moved to guarantee line of sight transmissions, the proposed strategy is potentially suitable for accurate positioning of a mobile object in an environment with a complex geometry. The system was tested experimentally, exhibiting a sub-centimeter positioning accuracy in a range up to 4 m.

This paper describes the design and realization of a 5.6 GHz ultra--wide bandwidth based position measurement system. The system has been entirely made using off--the-- shelf components and achieves centimeter level accuracy in an indoor environment. It is based on asynchronous modulated pulse round--trip--time measurements. Both system level and realization details are described along with experimental results including estimates of measurement uncertainties.

Estimation of periodic signals, based on quantized data, is a topic of general interest in the area of instrumentation and measurement. While several methods are available, new applications require low-power, low-complexity, and adequate estimation accuracy. In this paper, we consider the simplest possible quantization, that is binary quantization, and describe a technique to estimate the parameters of a sampled periodic signal, using a fast algorithm. By neglecting the possibility that the sampling process is triggered by some signal-derived event, sampling is assumed to be asynchronous, that is the ratio between the signal and the sampling periods is defined to be an irrational number. To preserve enough information at the quantizer output, additive Gaussian input noise is assumed as the information encoding mechanism. With respect to published techniques addressing the same problem, the proposed approach does not rely on the numerical estimation of the maximum likelihood function, but provides solutions that are very closed to this estimate. At the same time, since the main estimator is based on matrix inversion, it proves to be less time-consuming than the numerical maximization of the likelihood function, especially when solving problems with a large number of parameters. The estimation procedure is described in detail and validated using both simulation and experimental results. The estimator performance limitations are also highlighted.

In this paper, a technique for modeling propagation of Ultra Wide Band (UWB) signals in indoor or outdoor environments is proposed, supporting the design of a positioning systems based on Round Trip Time (RTT) measurements and on a particle filter. By assuming that nonlinear pulses are transmitted in an Additive White Gaussian Noise Channel, and detected using a threshold based receiver, it is shown that RTT measurements may be affected by a non-Gaussian noise. RTT noise properties are analyzed, and the effects of non-Gaussian noise on the performance of a RTT based positioning system are investigated. To this aim, a classical Least Square, an extended Kalman Filter and a Particle Filter are compared when used to detect a slowly moving target in presence of the modeled noise. It is shown that, in a realistic indoor environment, the Particle Filter solution may be a competitive solution, at a price of increased computational complexity. Experimental verifications validate the presented approach.

This paper has the main purpose to give an introductory survey on the various systems that exploit magnetic fields for positioning. Such systems find applications in those scenarios, both indoors and outdoors, where Global Navigation Satellite Systems (GNSS) are not available or fail to provide information with the needed accuracy. While the main idea of using electromagnetic fields to provide position information dates back to the past century, new application–led research on this topic has emerged in recent years. Results have expanded the application range of Magnetic Positioning (MP) technologies and form now a domain of knowledge that enables realization of positioning systems applicable to indoor and outdoor environments. The paper provides the main characteristics of different positioning systems with focus on those solutions that are based on low–frequency magnetic fields. Some background theory is presented and positioning results from the literature are analyzed and compared.

This paper introduces a novel procedure for quick estimation of the parameters of a sum of sinusoidal signals based on one-bit measurements. Amplitude, phases and, frequencies of the signal components are assumed unknown, as well as the threshold level of the comparator used to produce measurement results. To provide enough information at the one-bit quantizer input, a sinewave is assumed to dither one of the two comparator's inputs. To ease the procedure's application, only the peak-to-peak amplitude of this dither signal is assumed known. Theoretical, simulation-based and experimental results validate the presented approach.