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This article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the neural network and how the FNN is used in 2D and 3D position estimation process are presented. The most important results of the work are the parameters of various FNN network structures that resulted in a 100% probability of convergence of iterative position estimation algorithms in the exemplary TDoA positioning network, as well as the average and maximum number of iterations, which can give a general idea about the effectiveness of using neural networks to support the position estimation process. In all simulated scenarios, simple networks with a single hidden layer containing a dozen non-linear neurons turned out to be sufficient to solve the convergence problem. [ABSTRACT FROM AUTHOR]

This paper proposes an object location method for all types of applications, including the Internet of Things. The proposed method enables estimations of the position and orientation of an object on a plane or in space, especially during motion, by means of location signals transmitted simultaneously from two transmitters placed on the object at a known distance from each other. A mathematical analysis of the proposed method and Newton's algorithm for solving the system of nonlinear positional equations is presented. Next, an analysis of a position-dilution-of-precision parameter for the proposed method and a Cramer-Rao lower bound, limiting the accuracy of the method, is presented. Finally, the results of complex simulation studies on the efficiency of the proposed method are described. [ABSTRACT FROM AUTHOR]

Radiolocation systems for aviation based on Multi-Lateration (MLAT) typically use a set of synchronised ground sensors to receive radio signals broadcast by onboard transmitters. In most cases, the sensor synchronisation in Wide Area Multi-Lateration Systems (WAM) is provided by Global Navigation Satellite System (GNSS) receivers. However, in the case of synchronisation failure, there is still a possibility to estimate the coordinates of the tracked aircraft by using the measurements of the time of arrival taken by non-synchronised sensors. The article presents the principle of operation and equations for calculating the coordinates of an aircraft in an asynchronous multi-lateration system, together with the results of a computer simulation allowing comparison of the accuracy of position estimation between the asynchronous and the typical, synchronous MLAT. This paper contains also some comments on the required stability of the clock source for the sensors working in an asynchronous MLAT system. [ABSTRACT FROM AUTHOR]

This paper presents concept and implementation of digital phase-location system, designed as a navigational aid for marine applications. The main feature of the proposed system is the ability to work in both synchronous mode, with one master station and set of slave stations synchronised with master, and in asynchronous mode with independent clocking of all stations. [ABSTRACT FROM AUTHOR]

Radiating cables are mostly used to provide radio communication in tunnels or corridors, but they can also be used to estimate the position of a mobile terminal along the cable. In this paper, a measuring receiver's position was estimated by measuring the difference in the direct signal's reception time, which was generated by a transmitter connected to one end of the radiating cable, and the delayed signal retransmitted from another end. During tests, a relatively narrowband (23 MHz) signal was used in the unlicensed band (2.4 GHz) and 50 m long coupled mode radiating cable. The cable was installed along a corridor in the office building. Measurement results used different equipment configurations (i.e., return signal only amplified or amplified and frequency-shifted), which presented possible sources of errors. [ABSTRACT FROM AUTHOR]

This paper outlines a new method of a location service (LCS) in the asynchronous wireless networks (AWNs) where the nodes (base stations) operate asynchronously in relation to one another. This method, called asynchronous time difference of arrival (ATDOA), enables the calculation of the position of the mobile object (MO) through the measurements taken by a set of non-synchronized fixed nodes and is based on the measurement of the virtual distance difference between the reference nodes and the several MO positions (more than two), as well as on the solution of a nonlinear system of equations. The novelty of the proposed solution is using the measurements taken by at least five ground sensors without time synchronization between them to estimate the position of the tracked MO transmitting four or more sounding signals in random time.The new method significantly simplifies the localization process in real-life AWNs. It can be used on its own or to complement the traditional synchronous method. The paper focuses on the description of the proposed ATDOA method, two algorithms TS-LS (Taylor series least-squares) and GA (genetic algorithm) for solving the nonlinear system of equations, example application of the new method for a three-dimensional space, and presentation of the simulation models and simulation results. An important part of the paper is the comparison of the efficiency between the asynchronous method and the synchronous one for wide area multilateration (WAM) system. In addition, the Cramér-Rao lower bound (CRLB) is derived for this problem as a benchmark. The preliminary measurement results obtained by applying the proposed ATDOA method against the background of the synchronous one are presented at the end of the paper. As it could be expected, the synchronous solution gives better results. The synchronous method allows to locate the aircraft within 15 m in about 80% of the time, while the ATDOA method in 74% of the time for the base stations clocked from the reference clocks with the stability equal to 10−9, and in 58% of the time for the base stations clocked from the reference clocks with the stability equal to 10−8. The new method therefore should not be treated as the improvement of the existing synchronous positioning systems but as a backup solution which allows to keep the LCS systems running even during ground stations synchronization failure. [ABSTRACT FROM AUTHOR]

In this article a novel method of positional data integration in an indoor hybrid localization system combining inertial navigation with radio distance measurements is presented. A point of interest is the situation when the positional data and the radio distance measurements are obtained from less than thee reference nodes and it is impossible to unambiguously localize the moving person due to undetermined set of positional equations. The presented method allows to continuously provide localization service even in areas with disturbed propagation of the radio signals. Authors performed simulation and measurement studies of the proposed method to verify the precision of position estimation of a moving person in an indoor environment. It is worth noting that to determine the simulation parameters and realize the experimental studies the hybrid localization system demonstrator was developed, combining inertial navigation and radio distance measurements. In the proposed solution, results of distance measurements taken to less than three reference nodes are used to compensate the drift of the position estimated using the inertial sensor. In the obtained simulation and experimental results it was possible to reduce the localization error by nearly 50% regarding the case when only inertial navigation was used, additionally keeping the long term root mean square error at the level of ca. 0.50 m. That gives a degradation of localization precision below 0.1 m with respect to the fusion Kalman filtration when four reference nodes are present. [ABSTRACT FROM AUTHOR]

In this paper, an analytical model for slow and fast fading effects in maritime container terminals is derived, from fitting distributions to the results of measurements performed in an actual operational environment. The proposed model is composed of a set of equations, enabling to evaluate fading statistical distribution parameters for different system and environments conditions, as a function of frequency, base station antenna height, and average height of container stacks in a deepwater container terminal. The model's coefficients were obtained from a multivariate linear regression of the fitted distributions parameters, allowing to evaluate the different statistical distribution parameters with a negligible mean error and a standard deviation of the error less than 0.65 dB. It is observed that a good fitting is obtained for slow fading with the Lognormal Distribution, the standard deviation ranging in [1.40, 4.81] dB, while fast fading is well modeled by the Nakagami Distribution with the standard deviation ranging in [0.43, 1.26]. Hence, in a conservative perspective, values of 5 and 1.3 dB are proposed to characterize slow and fast fading, respectively. [ABSTRACT FROM AUTHOR]

This paper presents an off-body channel model for body area networks (BANs) in indoor environments. The proposed model, which is based on both simulations and measurements in a realistic environment, consists of three components: mean path loss, body shadowing, and multipath fading. Seven scenarios in a realistic indoor office environment containing typical scatterers have been measured: five were static (three standing and two sitting) and two dynamic (walk in a fixed place and real walk). The measurement equipment and measurement procedures are described. The mean path loss component is modeled as a log function of distance, the path loss exponent being in the range between 0.4 and 1.6, while a statistical perspective is taken for the other two components, i.e., body shadowing is found to be well modeled by a ognormal distribution and multipath fading by Rice or Nakagami- m distributions, depending on body motion characteristics. The correlation between the selected distributions and empirical data is not lower than 0.95, typically being greater than 0.98. The novelty of this model is that it takes the statistical influence of various parameters and features present in BANs into account, such as body influence, placement of the wearable antennas, user orientation in the environment, dynamism of the BAN scenario, and propagation conditions. [ABSTRACT FROM AUTHOR]

This paper presents an innovative method of locating airplanes, which uses only voice communication between an air traffic controller and the pilot of an aircraft. The proposed method is described in detail along with its practical implementation in the form of a technology demonstrator (proof of concept), included in the voice communication system (VCS). A complete analysis of the performance of the developed method is presented, including the results of simulation and measurement tests in real conditions. The obtained results are very optimistic and indicate that the proposed solution may constitute an alternative method of locating aircraft in emergency conditions, i.e., a backup solution in the case of failure of other positioning systems. [ABSTRACT FROM AUTHOR]

In this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on the basis of the measurement data for dynamic scenarios in an indoor environment. The obtained results clearly prove the validity of the proposed DL approach in the UWB WBANs and high (over 98.6% for most cases) efficiency for LOS and NLOS conditions classification. [ABSTRACT FROM AUTHOR]