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In this paper, a feasibility study of a shuntless coulomb counting method for estimating the state of charge (SOC) of a battery is presented. Contrary to conventional coulomb counting, the proposed method does not require an external resistive shunt; it instead only requires voltage measurements performed on the battery under test while it is operating. The current is measured indirectly using the battery’s equivalent series resistance (ESR). The method consists of a preliminary calibration phase where the ESR and the open-circuit voltage of the battery are measured for different SOCs and stored in look-up tables (LUTs). Then, in the subsequent operational phase, the method uses these LUTs together with the measured voltage at the battery terminals to estimate the SOC. The performance of the proposed method is evaluated on a sample lithium polymer (LiPo) battery, using a realistic current profile derived from the Worldwide Harmonized Light-Duty Vehicles Test Procedure (WLTP). The results of this experimental evaluation demonstrate a SOC estimation root-mean-square error of 0.82% and a maximum SOC error of 1.45%. These results prove that the proposed method is feasible in a practical scenario.

In this article, 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 the 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 the 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 non-line-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 number 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 article introduces a novel procedure for the estimation of the frequency, amplitude, and phase of a sinusoidal signal after one-bit quantization. The estimator requires knowledge of the quantizer threshold but does not require information about the noise probability density function (PDF), possibly affecting measurement results. The threshold must be different from zero for estimating the amplitude but not necessarily for estimating the frequency or the phase. The algorithm requires an irrational value of the ratio between the sinusoidal frequency and the sampling rate. The procedure allows also the estimation of the noise variance and the cumulative distribution function (CDF). Theoretical properties are analyzed, and experimental results are provided to validate the estimation procedure.

We present an in-circuit approach for estimating the $LC$ parameter in coupled resonant circuits. The theoretical background is discussed by presenting the models and performing a numerical sensitivity analysis. The method for estimating $LC$ is based on noisy frequency response function measurements of the coupled resonant circuit. A practical implementation is presented and employed to validate the proposed method. Experimental results show that the proposed method provides an estimate of $LC$ with a deviation of less than 4% with respect to $LCR$ meter measurement results.

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 $15\;\text{m} \times 12\;\text{m}$ in NLOS conditions. Similar performance is obtained in an outdoor environment over an area of $30\;\text{m} \times 14\;\text{m}$ . 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.

Reliable diagnosis of early-stage Parkinson’s disease is an important task, since it permits the administration of a timely treatment, slowing the progression of the disease. Together with non-motor symptoms, other important signs of disease can be retrieved from the measurement of the movement trajectory and from tremor appearances. To measure these signs, the paper proposes a magnetic tracking system able to collect information about translational and vibrational movements in a spatial cubic domain, using a low-cost, low-power and highly accurate solution. These features allow the usage of the proposed technology to realize a portable monitoring system, that may be operated at home or in general practices, enabling telemedicine and preventing saturation of large neurological centers. Validation is based on three tests: movement trajectory tracking, a rest tremor test and a finger tapping test. These tests are considered in the Unified Parkinson’s Disease Rating Scale and are provided as case studies to prove the system’s capabilities to track and detect tremor frequencies. In the case of the tapping test, a preliminary classification scheme is also proposed to discriminate between healthy and ill patients. No human patients are involved in the tests, and most cases are emulated by means of a robotic arm, suitably driven to perform required tasks. Tapping test results show a classification accuracy of about 93% using a k-NN classification algorithm, while imposed tremor frequencies have been correctly detected by the system in the other two tests.

This article presents a compact measurement system for electrochemical impedance spectroscopy (EIS) on lithium-ion battery (LIB). The system is composed of a vector impedance analyzer (VIA) and state parameter estimation. The VIA architecture is based on delta–sigma digital-to-analog and analog-to-digital conversions to achieve the compactness, low-power consumption, and high resolution required to be potentially integrated within a battery cell. The estimation of state parameters is based on equivalent circuit models and the solution of nonlinear optimization problems. The proposed measurement system aims at the integration of complex measurement features directly into the battery cell to allow online and real-time diagnostic of the battery cell. A prototype of the compact measurement system was realized to assess the proposed approach. Experimental results are provided and validated by comparison with a reference laboratory instrument, showing good agreement. The VIA prototype is experimentally tested in both the online monitoring and aging monitoring of a commercial LIR2032 LIB cell. The modeling approach is applied to the experimental data provided by the VIA prototype, showing a good fit of the data. Moreover, parameters of the equivalent circuit models are extracted from the experimental data provided by the VIA prototype and identify trends related to the state of charge of the battery.

A detection method for parametric signals in noise is proposed. Since the detection is performed by processing 1-bit quantized data, the method can be implemented using low-complexity systems. A generalized likelihood ratio test (GLRT) is derived, which is based on parametric estimates of the amplitude and phase of a periodic signal. The asymptotic properties of the test statistic of the GLRT are derived analytically. Such properties are then employed to study the performance of the detector, by comparing them with the clairvoyant detector. The performance of the developed detector is evaluated by numerical simulations and validated by a simple experimental setup. The impact of noise and threshold selection on detection performance and the promptness of response are also numerically analyzed. Given its implementation simplicity, the proposed detector does not require high-resolution circuitry nor computationally intensive hardware. Therefore, it could enable novel applications in the Internet-of-Things domain, such as low-cost radar systems and sensor networks.

Gesture recognition is a fundamental step to enable efficient communication for the deaf through the automated translation of sign language. This work proposes the usage of a high-precision magnetic positioning system for 3D positioning and orientation tracking of the fingers and hands palm. The gesture is reconstructed by the MagIK (magnetic and inverse kinematics) method and then processed by a deep learning gesture classification model trained to recognize the gestures associated with the sign language alphabet. Results confirm the limits of vision-based systems and show that the proposed method based on hand skeleton reconstruction has good generalization properties. The proposed system, which combines sensor-based gesture acquisition and deep learning techniques for gesture recognition, provides a 100% classification accuracy, signer independent, after a few hours of training using transfer learning technique on well-known ResNet CNN architecture. The proposed classification model training method can be applied to other sensor-based gesture tracking systems and other applications, regardless of the specific data acquisition technology.

This article introduces a novel procedure for quick estimation of the parameters of a sum of sinusoidal signals based on 1-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 1-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.

We present a short-range magnetic positioning system that can track in real-time both the position and attitude (i.e., the orientation of the principal axes of an object in space) of up to six moving nodes. Moving nodes are small solenoids coupled with a capacitor (resonant circuit) and supplied with an oscillating voltage. Active moving nodes are detected by measuring the voltage that they induce on a three-dimensional matrix of passive coils. Data on each receiving coil are acquired simultaneously by a distributed data-acquisition architecture. Then, they are sent to a computer that calculates the position and attitude of each moving node. The entire process is run in real-time: the system can perform 62 position and attitude measurements per second when tracking six nodes simultaneously and up to 124 measurements per second when tracking one node only. Different active nodes are identified using a frequency-division multiple access technique. The position and angular resolution of the system have been experimentally estimated by tracking active nodes along a reference trajectory traced by a robotic arm. The factors limiting the viability of upscaling the system with more than six active nodes are discussed.

The parametric estimation of devices in a signal chain, including the cascade of a digital-to-analog converter (DAC), a low-pass filter, and an analog-to-digital converter (ADC), is considered in this article. Frequency- and amplitude-domain procedures are presented for the estimation of the DAC output levels and ADC transition levels connected in a loopback configuration, including a low-pass filter in-between. A special class of source signals is used to perform estimation of the DAC and filter parameters. Estimation is based on a selection of excited frequencies to avoid uncertainties caused by DAC nonlinearities. An amplitude-domain estimator is used to measure the ADC integral nonlinearities by using the empirical distribution function of the ADC input signal. It is shown that high estimation accuracy can be achieved for all identifiable parameters in the signal chain. Theoretical, simulation, and experimental results are presented to validate the proposed procedure.

This paper describes the development of a distributed sensing system that can be disseminated in an environment of interest to monitor the vibration of a structure. This low-cost system consists of several sensor nodes and a central receiving node. All nodes are built using off-the-shelf electronic components. Each of the sensor nodes is battery-powered and equipped with a triaxial MEMS accelerometer, a wireless Long Range (LoRa) transceiver module for data transmission, a GPS module used for synchronization, and a microcontroller. The operation of the sensor node is validated by controlled laboratory tests where it is compared to a commercial reference accelerometer. Furthermore, the feasibility and potential benefits of the application of the proposed system to a structure in an archaeological site is investigated. Results show that the proposed sensor node could successfully monitor the vibration at several locations within the site. Therefore, it may be employed to detect the most relevant stresses to the structure, allowing for the identification of risks.

In this paper, two techniques for accurate estimation of the moment of magnetic dipole are proposed. The achievable accuracy is investigated, as a function of measurement noise affecting estimation of magnetic field cartesian components, and with respect to the induced rms voltage. The proposed techniques are validated both via simulations and experiments.

Many distributed systems that perform indoor positioning are often based on ultrasound signals and time domain measurements exchanged between low-cost ultrasound transceivers. Synchronization between transmitters and receivers is usually needed. In this paper, the use of BLE technology to achieve time synchronization by wirelessly triggered ultrasound transceivers is analyzed. Building on a previous work, the proposed solution uses BLE technology as communication infrastructure and achieves a level of synchronization compatible with Time of Flight (ToF)-based distance estimations and positioning. The proposed solution was validated experimentally. First, a measurement campaign of the time-synchronization delay for the adopted embedded platforms was carried out. Then, ToF-based distance estimations and positioning were performed. The results show that an accurate and low-cost ToF-based positioning system is achievable, using ultrasound transmissions and triggered by BLE RF transmissions.

Meaningful information on the internal state of a battery can be derived by measuring its impedance. Accordingly, battery management systems based on electrochemical impedance spectroscopy are now recognized as a feasible solutions for online battery control and diagnostic. Since the impedance of a battery is always changing along with its state of charge and aging effects, it is important to have a stable impedance reference in order to calibrate and test a battery management system. In this work we propose a programmable impedance emulator that in principle could be used for the calibration of any battery management system based on electrochemical impedance spectroscopy. A digital finite-impulse-response filter is implemented, whose frequency response is programmed so as to reproduce exactly the impedance of a real battery in the frequency domain. The whole design process of the filter is presented in detail. An analytical expression for the impedance of real battery in the frequency domain is derived from an equivalent circuit model. The model is validated both through numerical simulations and experimental tests. In particular, the filter is implemented on a low-cost microcontroller unit, and the emulated impedance is measured by means of a custom-made electrochemical impedance spectroscopy measuring system, and verified by using standard commercial bench instruments. Results on this prototype show the feasibility of using the proposed emulator as a fully controllable and low-cost reference for calibrating battery impedance measurement systems.

In this paper, simultaneous amplitude measurement of multiple Linear Chirp Signals (LCSs) is discussed, with the main aim of supporting the development of tracking systems based on Received Signal Strength measurements, capable of tracking multiple targets. LCSs are assumed to be generated by digital devices whose clocks are not fully synchronized. Effects of partial synchronization and noise at the receiver side are investigated and discussed, assuming that the signals’ amplitudes are estimated using correlation techniques. Moreover, effect of quantization is discussed, and the effects of a mismatch in the sampling frequency of LCSs feeding the estimation algorithm are deeply analyzed and modeled. It is shown that using interpolation techniques does not significantly improve the estimation accuracy. Moreover, in the presence of frequency mismatches using long LCSs does not lead to increased accuracy. Finally, frequency accuracy of currently available microcontroller units may permit practical implementations of the proposed solution.

This paper investigates the applicability of a developed Magnetic Positioning System (MPS) as a support for a dead-reckoning inertial navigation system (DR-INS) for pedestrian applications. The integrated system combines the complementary properties of the separate systems, operating over long periods of time and in cluttered indoor areas with partial nonline-of-sight conditions. The obtained results show that the proposed approach can effectively improve the coverage area of the MPS and the operation time with bounded errors of the DR-INS. In particular, a solution that provides bounded position errors of 1–2 m over significantly long periods of time up to 45 min, in realistic indoor environments, is demonstrated. Moreover, system applicability is also shown in those scenarios where arbitrary orientations of the MPS mobile node are considered and an MPS position estimate is not available due to less than three distance measurements.

This paper proposes an analysis of the quasi-stationary magnetic field generated by coils and its applicability to 3-D short-range positioning scenarios. Starting from a theoretical background, an approximation of the induced voltage in a sensor coil is developed and analyzed. Then, the design and performance of a short-range magnetic field-based positioning system is described. The system is realized by using three-axis field generating coils and a three-axis sensor coil. It uses resonance properties to decrease current and power consumption requirements. The system is targeted for simple and low-cost applications, requiring subdecimeter accuracies over short ranges of approximately a couple of meters. The realized prototype, validated through in-field measurements, features a positioning error in the order of 4–5 cm over an area of 1.15 m $\times $ 1.55 m $\times $ 0.8 m.

The influence of the environmental configuration on ac magnetic distance and position measurement systems, which are based on inductive coupling of tuned resonators, is experimentally analyzed. The main aspects that affect the accuracy of such systems are the conductivity of the terrain and the presence of metallic materials near the resonators. It is shown that such aspects are frequency dependent, and a tradeoff is to be considered between the maximum operating range and the error. Moreover, a strategy to detect if the measurement results are corrupted by the environmental configuration is presented. The analysis is then extended to a positioning scenario where the prototype of a magnetic positioning system (MPS) is deployed and a comparison with a commercial ultrawideband (UWB) system is performed. The results show that the MPS performance is comparable with the commercial UWB system, leading to a mean positioning error of the order of 0.6 m when using an extended Kalman filter-based positioning algorithm.

In this paper, a robotic arm moving along a user-defined trajectory is used to calibrate a short-range magnetic positioning system (MPS). Such system estimates the position and attitude of an active transmitting coil by measuring the induced voltage on a set of fixed receiving coils, with known position and orientation. This estimate is obtained by solving an optimization problem that can be decomposed into a linear and a reduced nonlinear problem. Then, a Kalman Filter is used to process the estimated positions and obtain smooth trajectories. Data acquisition and processing are performed in real time by the MPS. In this context, the robotic arm is used to provide ground truth, i.e., to move the active coil along a known trajectory, while simultaneously the MPS estimates the position of the active coil. Such ground-truth information is then used to calibrate the MPS and improve its accuracy. To align the robotic arm with the MPS, a preliminary calibration procedure of the robot is performed. Then, a wide ground-truth trajectory is used to estimate the calibration parameters of the MPS itself, namely, the positions and orientation of the fixed coils. To validate the efficiency of the calibration procedure, the accuracy of the MPS is evaluated across several trajectories. The results show that the mean positioning error is less than 3 mm. Finally, an on-the-fly calibration method simultaneously estimating positions and attitudes of both the active coil and all the receivers is investigated.

In this article, the amplitude measurement of multiple and simultaneously received linear chirp signals is investigated. The achievable scalability, that is, the maximum number of simultaneously transmitted superimposed signals that a receiver can characterize with a given target accuracy, is explored using simulations. The effect of chirp duration and bandwidth on the estimation accuracy and on the scalability is investigated. The effect of inaccuracies affecting the realized chirp duration and bandwidth is also discussed. It is shown that the scalability of the proposed approach is competitive with respect to multiple access methods, such as frequency-division multiple access or code-division multiple access. It is also shown that accurate amplitude measurements are achievable even when the collected signal is the superimposition of up to 20 chirp signals with amplitudes differing by three orders of magnitude.

Time-interval measurement systems using threshold detectors experience severe performance degradation in the presence of noise and interference. This paper describes an approach to robust measurement of time intervals in the presence of interference. This approach is based on modeling the distribution of the measurement results as a Gaussian–uniform mixture. A batch maximum-likelihood and a recursive particle filtering estimator are implemented, which incorporate the above model. The accuracy and robustness of the approach are evaluated by numerical simulations and by comparison with the Cramer–Rao lower bound. Finally, as a case study, the approach is applied to the experimental data obtained from an in-house developed ultrawideband time-interval measurement system.

In this article, it is shown how to estimate the frequency response function of a linear system using a three-level digital-to-analog converter (DAC) and a 1-bit analog-to-digital converter (ADC). Estimation requires the usage of a three-level periodic stimulus signal and a sinewave, used as a dither signal to improve the effective resolution of the 1-bit ADC. By a suitable choice of the source sequence, the proposed procedure is robust to nonlinearities in the used DAC and allows detection of nonlinearities affecting the linear filter output. This article illustrates the main idea, its theoretical aspects, the system design parameters, and simulation and experimental results, obtained in the case of a passive low-pass filter.

Several issues related to the practical synthesis of ternary sequences with specified spectra are addressed in this paper. Specifically, sequences with harmonic multiples of two and three suppressed are studied, given their relevance when testing and characterizing nonlinear systems. In particular, the effect of non-uniform Digital to Analog Converter (DAC) levels on the spectral properties of the generated signal is analyzed. It is analytically shown that the DAC non-uniform levels result in degraded harmonic suppression performance. Moreover, a new approach is proposed for designing ternary sequences, which is flexible and can be adapted to suit different requirements. The resulting sequences, denoted as randomized constrained sequences, are characterized theoretically by deriving an analytical expression of the power spectral density. Furthermore, they are extensively compared with three synthesis approaches proposed in the literature. The approach is validated by numerical simulations and experimental results, showing the potential to achieve harmonic suppression performance of approximately 100 dB.

The problem of measuring the best linear approximation of a nonlinear system by means of multilevel excitation sequences is analyzed. A comparison between different types of sequences applied at the input of Wiener systems is provided by numerical simulations and by experiments on a practical circuit including an analog filter and a clipping nonlinearity. The performance of the sequences is compared with a white Gaussian noise signal for reference purposes. The theoretical characterization of the best linear approximation when using randomized constrained sequences is derived analytically for the cubic nonlinearity case. Numerical and experimental results show that the randomized constrained approach for designing ternary sequences has a low sensitivity to both even and odd order nonlinearities, resulting in a response close to the actual response of the underlying linear system., Comment: Accepted for Publication in IEEE Transactions on Instrumentation and Measurement

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.

This paper provides 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 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 technologies and form now a domain of knowledge that enables realization of positioning systems applicable to indoor and outdoor environments. This 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.

Advantages of inductively coupled links for short-range communications are well known. Recently, they gained popularity as a viable solution for wireless power transmission. Interesting to notice that data communication capability is required as well, mainly for coordinating the transfer process. In this paper, the authors address the use of chirp signaling over inductively coupled links for both time dissemination and data communications. Such an approach extends field of applications, including data acquisition and instrumentation that are used in industrial automation. The effectiveness of the proposed approach is verified with extensive simulations and using a proof-of-concept prototype. Despite the prototype simplicity, jitter on the synchronizing reference signal is in the order of few microseconds and the bit error rate, over a short distance, is negligible.

This paper presents research to develop an ultrawideband ranging sensor for personnel indoor localization based on the measurement of the pulse round-trip time. An approach combining flexibility, a high measurement update rate, and asynchronous operation with digital processing capability has been employed in the design of the sensor. The principle of operation, the architecture of the realized sensor, and the experimental setup are described. Finally, the results of a ranging calibration and validation test are presented and discussed. In the validation procedure, a root-mean-square error of 29 cm and a maximum absolute error of 81 cm with an operational range of approximately 10 m were observed.

A method for crosstalk detection and removal in multichannel time-of-arrival measurement systems is proposed. The method, based on low-complexity processing of cross-correlation results, is evaluated by numerical simulations and experimental characterization. Results show the capability to detect and remove crosstalk by processing the signals acquired by two mutually-interfering electrical channels. The validation, carried out on a time-of-arrival positioning system, yielded centimeter-level accuracy in the presence of relevant inter-channel interference. The proposed method is of a general nature and is not limited only to positioning scenarios.

This paper proposes an analysis of the quasi-stationary magnetic field generated by coils and its applicability to 3D positioning applications. Starting from a theoretical background, an approximation of the induced voltage in a sensor coil is developed and analyzed. In particular, the introduced approximation error is shown to be lower than 5 mm over a 20 m range. Finally, the developed model is compared against a well-established theoretical model developed in the literature and against in-field measurements in the range 0.5 m to 5 m. Results show that the developed model may be suitable for magnetic field based distance measurements in low complexity 3D positioning applications.

A new circuit-based method for performance evaluation of mid-range wireless power transfer links is presented. The characterization is based on the measurement of selected node voltages, which allows to define the performance of the link in terms of its efficiency, output power, and mutual inductance. The main feature of the proposed method is that it can be applied to wireless power transfer systems during normal operational conditions, without the need for disconnecting the load. The characterization procedure is validated by experimental results.

This paper describes the design and realization of a magnetic positioning system (MPS) integrated with a global positioning system (GPS) receiver. The GPS receiver is composed of hardware and software sections that can be integrated with the MPS. Both system-level architecture and realization details are described along with experimental results. The realized prototype measurement system exhibits a maximum positioning error of less than 5 m and an average error of less than 3 m, thus providing better performance than a stand-alone GPS consumer receiver. Further, the system is tested in two different scenarios, showing repeatable performance. A practical system implementation is presented, which can be employed in applications that require power-efficiency and low-cost operation. Such an implementation is tested experimentally, providing results that are comparable to those of the preliminary prototype, thus validating the proposed approach.

This paper addresses the problem of adaptive noise cancellation in a multi-channel system. The proposed canceller is a recursive system, based on the Least Mean Squares filter (LMS). This method is analyzed by simulations and experimental results are given. Specifically, it is shown that this technique can improve the accuracy of ultrasound ranging and positioning systems using multichannel receivers.

This paper describes the design and realization of a Magnetic Positioning System (MPS) integrated with a Global Positioning System (GPS) receiver. The GPS receiver is composed of a hardware section and a software section that can integrate with the MPS. Both system-level architecture and realization details are described along with experimental results. The realized measurement system exhibits a maximum positioning error of less than 5 m, and an average error of less than 3 m, thus providing better performance than a standalone GPS consumer receiver. Further, the system has been tested in two different scenarios, showing repeatable performance.

Accurate estimation of the position of network nodes is essential, e.g., in localization, geographic routing, and vehicular networks. Unfortunately, typical positioning techniques based on ranging or on velocity and angular measurements are inherently limited. To overcome the limitations of specific positioning techniques, the fusion of multiple and heterogeneous sensor information is an appealing strategy. In this paper, we investigate the fundamental performance of linear fusion of multiple measurements of the position of mobile nodes, and propose a new distributed recursive position estimator. The Cram\'er-Rao lower bounds for the parametric and a-posteriori cases are investigated. The proposed estimator combines information coming from ranging, speed, and angular measurements, which is jointly fused by a Pareto optimization problem where the mean and the variance of the localization error are simultaneously minimized. A distinguished feature of the method is that it assumes a very simple dynamical model of the mobility and therefore it is applicable to a large number of scenarios providing good performance. The main challenge is the characterization of the statistical information needed to model the Fisher information matrix and the Pareto optimization problem. The proposed analysis is validated by Monte Carlo simulations, and the performance is compared to several Kalman-based filters, commonly employed for localization and sensor fusion. Simulation results show that the proposed estimator outperforms the traditional approaches that are based on the extended Kalman filter when no assumption on the model of motion is used. In such a scenario, better performance is achieved by the proposed method, but at the price of an increased computational complexity., Comment: IEEE Journal on Selected Areas in Communications (To Appear), 2015

In this paper we develop a new technique for estimating fine clock errors and range between two nodes simultaneously by two-way time-of-arrival measurements us- ing impulse-radio ultra-wideband signals. Estimators for clock parameters and the range are proposed that are robust with respect to outliers. They are analyzed numerically and by means of experimental measurement campaigns. The technique and derived estimators achieve accuracies below 1Hz for frequency estimation, below 1 ns for phase estimation and 20 cm for range estimation, at 4m distance using 100MHz clocks at both nodes. Therefore, we show that the proposed joint approach is practical and can simultaneously provide clock synchronization and positioning in an experimental system., Comment: IEEE Journal on Selected Areas in Communications (Accepted)

The influence of the environmental configuration on AC magnetic distance-measurement systems, which are based on inductive coupling of tuned resonators, is experimentally analyzed. The main aspects that affect accuracy in such systems are the conductivity of the terrain and the presence of metallic materials near the resonators. It is shown that such aspects are frequency-dependent, and a tradeoff is to be considered between maximum operating range and error. Moreover, a strategy to detect if measurement results are corrupted by environmental configuration is presented. This strategy is crucial to improve the integrity of positioning systems.

The knowledge of the time value at which an event of interest occurred is the typical feature needed to perform many kinds of postprocessing in distributed sensor networks. Consequently, network-based distributed systems must support time dissemination in order to ensure that relative clock errors among nodes remain below a certain threshold. Despite many protocols being well established for wired connections, the wireless sensor network paradigm required a new approach to address adverse characteristics of the wireless medium. In this paper, the adoption of low-frequency signaling is proposed for overcoming some issues of radio frequency transmissions when used for timestamping events. The proposed approach is characterized using numerical simulations and an experimental prototype, based on inductive coupling of tuned resonators. Experimental tests confirm the effectiveness and feasibility of this approach that achieves microsecond-order time recovery performance in practical system configurations.

Estimating the position of a mobile node by linear sensor fusion of ranging, speed, and orientation measurements has the potentiality to achieve high localization accuracy. Nevertheless, the design of these sensor fusion algorithms is uncertain if their fundamental limitations are unknown. Despite the substantial research focus on these sensor fusion methods, the characterization of the Cramer Rao Lower Bound (CRLB) has not yet been satisfactorily addressed. In this paper, the existence and derivation of the posterior CRLB for the linear sensor fusion of ranging, speed, and orientation measurements is investigated. The major difficulty in the analysis is that ranging and orientation are not linearly related to the position, which makes it hard to derive the posterior CRLB. This difficulty is overcome by introducing the concept of posterior CRLB in the Cauchy principal value sense and deriving explicit upper and lower bounds to the posteriori Fisher information matrix. Numerical simulation results are provided for both the parametric CRLB and the posterior CRLB, comparing some widely-used methods from the literature to the derived bound. It is shown that many existing methods based on Kalman filtering may be far from the the fundamental limitations given by the CRLB.

In this paper, we consider magnetic positioning and tracking of objects and provide a comparison of the characteristics of two major measurement models: the magnetic dipole model and the mutual inductance model. The numerical results obtained by applying these models to a short-range position measurement application, with a maximum operating distance of approximately 50 cm, are compared. Based on the results of this comparison, a prototype 9-sensor array is developed, experimental tests are performed, and extensive measurement results are presented. Outcomes show the feasibility of tracking the position and orientation of a mobile coil in real time with a median positioning error below 1 cm and a worst-case error of about 2 cm and 11 degrees inside a spatial region of 30 × 30 × 30 cm³ operational volume.