Transmitter Locations Research Articles

RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks

In this paper we propose a highly efficient and very accurate deep learning method for estimating the propagation pathloss from a point x (transmitter location) to any point y on a planar domain. For applications such as user-cell site association and device-to-device link scheduling, an accurate knowledge of the pathloss function for all pairs of transmitter-receiver locations is very important. Commonly used statistical models approximate the pathloss as a decaying function of the distance between transmitter and receiver. However, in realistic propagation environments characterized by the presence of buildings, street canyons, and objects at different heights, such radial-symmetric functions yield very misleading results. In this paper we show that properly designed and trained deep neural networks are able to learn how to estimate the pathloss function, given an urban environment, in a very accurate and computationally efficient manner. Our proposed method, termed RadioUNet, learns from a physical simulation dataset, and generates pathloss estimations that are very close to the simulations, but are much faster to compute for real-time applications. Moreover, we propose methods for transferring what was learned from simulations to real-life. Numerical results show that our method significantly outperforms previously proposed methods.

A Spatial Sparse Method for Mobile Localization of Multiple Co-Channel Transmitters

Co-channel signals tracking is an important topic in the field of radio monitoring. A direct tracking method based on random spatial spectrum is proposed for multiple mobile co-channel transmitters. The co-channel signals completely overlap in both time and frequency domains, but can be separated in the spatial domain. The random spatial spectrum is derived based on a set of state particles. The spatial sparse method is then proposed to track the positions based on the sparsity of a grid spatial spectrum. The algorithm is verified by the constant turn rate and acceleration motion model. Simulation results are given to demonstrate that the proposed algorithm outperforms other tracking algorithms and provide robust locating performance for multiple co-channel targets with different received powers.

Narrowband PLC Channel Attenuation Due to a Multi-Grounded Neutral

This paper presents a theoretical study on the influence of a multi-grounded neutral on the transmission of narrowband power-line communication (PLC) signals through a two-wire medium-voltage distribution line. Three different methods are proposed to calculate the transfer function of the line in the 3-500 kHz range: (i) nodal admittance method; (ii) travelling wave method; (iii) electrically-short line approach. The validity, advantages and shortcomings of each method are presented and discussed. It is shown that improving the grounding impedance at the transmitter and receiver locations will contribute to reducing the channel attenuation. It is also shown that the number of intermediate grounding points along the neutral is more relevant for the attenuation of PLC signals than their impedance. In general, increasing such number will always reduce the attenuation in frequencies where the line is electrically short. A similar behavior is observed at the higher end of the 3-500 kHz range provided the grounding interval is less than 300 m, which is half wavelength of the 500 kHz frequency. If the separation between grounding points is greater than that, reducing the number of grounding points is likely to reduce the average channel attenuation, but at the cost of introducing multiple resonant frequencies.

A probabilistic‐based approach for direction‐of‐arrival estimation and localization of multiple sources

SummaryThis article contributes to science at two points. The first contribution is at a point of introducing a novel direction‐of‐arrival (DOA) estimation method which based on subspaces methods called Probabilistic Estimation of Several Signals (PRESS). The PRESS method provides higher resolution and DOA accuracy than current models. Second contribution of the article is at a point of localizing the unknown signal source. The process of localization achieved by using DOA information for the first time. The importance of localization exists in a large area of engineering applications. The aim is to determine the location of multiple sources by using PRESS with minimum effort of computation. We used the maximum probabilistic process in this study. Initially, all the signals are collected by the array of sensors and accurately identified using the proposed algorithm. The receiver at the best in test estimates the source location using only the knowledge of the geographical latitude and longitude values of the array of sensors. Several test points with an accurately calculated angle of arrival enable us to draw linear lines towards the transmitter. The transmitter location can be accurately identified with the line of interceptions. Simulation and numerical results show the outstanding performance of both the DOA estimation method and transmitter localization approach compared with many classical and new DOA estimation methods. The PRESS localization method first tested at 19°, 26°, and 35° with an signal‐to‐noise ratio (SNR) value of ‐5 dB. The PRESS method produced results with an extremely low bias of 0 and 0.00080°. The simulation tests are repeated and produced results with zero bias, which give the exact location of the unknown source.

Simulated high frequency ray paths considering traveling ionospheric disturbances

This study presents a modified version of a classical 3-D numerical ray tracing code [originally by Jones and Stephenson (A versatile three-dimensional ray tracing computer program for radio waves in the ionosphere. Office of Telecommunications Report 75–76, US Government Printing Office, Washington, DC, 1975)], now linked to ionosphere, neutral atmosphere, Earth’s magnetic field, and traveling ionospheric disturbances (TIDs) models. This method is applied to study the effect of TIDs on radio waves by simulating the waves’ propagation in a disturbed ionosphere. A 3-D cubic interpolation method is implemented in the ray tracing code to solve discontinuities and guarantee the ray tracing validity and accuracy under all conditions. Changes of the ground range distance (R) and the bearing angle (σ) are assessed for various simulated ray paths. A Pedersen ray case is also shown, for which small changes of signal frequency lead to enhanced variations. The study of HF ray path variations in terms of various TIDs characteristics and under different background ionospheric conditions and transmitter locations and radiation pattern can contribute to the mitigation of TIDs effects, either helping to improve existing methods or to develop new ones. The 3-D ray tracing code described and implemented in this work may well work for this purpose.

Non-line-of-sight error mitigating algorithms for transmitter localization based on hybrid TOA/RSSI measurements

Rendezvous control of multiple robots without losing network connectivity has important implications in multi-robot system including formation control, coordinated task assignments, and cooperative robotic missions. This paper introduces a new coordinate-free, bearing-based algorithm to enable rendezvous of distributed mobile robots at any designated leader robot node using hierarchical tracking of wireless network topology. An assumption is made that the robot can only sense and communicate with their neighbors (i.e., local sensing). The proposed approach preserves connectivity during the rendezvous task, adapts to dynamic changes in the network topology (e.g., losing or re-gaining a communication link), and is tolerant of mobility faults in the robots. We theoretically analyze the proposed algorithm and experimentally demonstrate the approach through simulations and extensive field experiments. The results indicate that the method is effective in a variety of realistic scenarios in which the robots are distributed in a cluttered environment.

Multipath Assisted Positioning With Transmitter Visibility Information

In multipath assisted positioning, multipath components (MPCs) are regarded as line-of-sight (LoS) signals from virtual transmitters. Instead of trying to mitigate the influence of MPCs, the spatial information contained in MPCs is exploited for localization. The locations of the physical and virtual transmitters are in general unknown but can be estimated with simultaneous localization and mapping (SLAM). Recently, a multipath assisted positioning algorithm named Channel-SLAM for terrestrial radio signals has been introduced. It simultaneously tracks the position of a receiver and maps the locations of physical and virtual radio transmitters. Maps of estimated transmitter locations can be augmented by additional information. Within this paper, we propose to extend the Channel-SLAM algorithm by mapping information about the visibility of transmitters. A physical or virtual transmitter is visible, if its signal is received in a LoS condition. We derive a novel particle filter for Channel-SLAM that estimates and exploits visibility information on transmitters in addition to their locations. We show by means of simulations in an indoor scenario that our novel particle filter improves the positioning performance of Channel-SLAM considerably.

An Adaptive Vector Median Filtering Approach to Enhance the Prediction Efficiency of Signal Power Loss

This research work designed and implemented an adaptive Artificial Neural Network (ANN) model using Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) models built on a Vector Median Filter (VMF) for pre-processing of the dataset. Normalized dataset is denoised using VMF and trained with both MLP- and RBF-ANN models. The proposed model has been developed from measurement data collected from two transmitter locations of non-line-of-sight and line-of-sight operating at the 1900MHz frequency band from LTE cellular network over distances of 1800m 1400m respectively. For non-line-of-sight site-1, VMF-MLP gives a correlation coefficient of 0.9600 compared to 0.9490 for VMF-RBF with a Bayesian regularization training algorithm. The VMF-MLP has 2.1380, 1.5000, and 1.4510 for root mean squared error, mean absolute error, and standard deviation compared to 2.3550, 1.5370, and 1.5610 for VMF-RBF network, respectively. The same trend was seen for line-of-sight in site-2 where correlation coefficient for VMF-MLP is 0.9900 and for VMF-RBF is 0.9840. The VMF-MLP has root mean squared error, mean absolute error, and standard deviation as 2.0670, 1.4900, and 1.3180, respectively, compared to VMF-RBF as 2.3470, 1.9010, and 1.3760, respectively. The predictions of these measurement data have been analyzed in this research work.

In-Situ Calibration of Antenna Arrays Within Wireless Locating Systems

Antenna arrays are frequently used for localization of active communication transmitters or passively reflecting radar targets by evaluating signal phases at spatially distributed antennas. Unfortunately, the localization performance is degraded because of mutual coupling, unknown time delays, and imprecisely known antenna positions, especially if large arrays with spatially distributed antennas are used. Furthermore, these errors are altered until the array is steadily installed at its destination, which occurs because of position misalignment and cable phase instability. Hence, an in-situ array calibration is necessary to perform faultless phase measurements. For this purpose, this article proposes a novel calibration procedure for antenna arrays, correcting both the mutual coupling and positioning errors using an incoherently transmitting beacon. Because the in-situ calibration will be affected by multipath, measurements at random reference positions within the array’s near field are used for calibration. In addition, the algorithm copes with randomly varying path losses because of unknown antenna polarizations and patterns. Calibration measurements are performed, providing physically reasonable results without using an anechoic environment. Furthermore, the calibration results are validated via indoor localization using three antenna arrays that were calibrated with the proposed algorithm.

Focusing Arc-Array Bistatic Synthetic Aperture Radar Data Based on Keystone Transform

Arc-array synthetic aperture radar (AA-SAR) has become a novel imaging scheme for full azimuth observation. However, the exiting arc-array monostatic SAR system is placed on a single platform and is easy to detect. Arc-array bistatic SAR (AA-BiSAR) with a stationary transmitter is proposed in this paper, which can obtain high data acquisition efficiency and reduce vulnerability of arc-array monostatic SAR. Furthermore, since the azimuth resolution with full azimuth observation is not related to the location of the stationary transmitter, the transmitter can be placed far away from the receiver. Compared with imaging algorithms for other modes, the key points of AA-BiSAR imaging algorithms are a square root in the bistatic slant range equation and an arc synthetic array in azimuth. According to the imaging geometry of AA-BiSAR, a novel imaging approach for AA-BiSAR based on keystone transform (KT) is proposed, and the KT implements range-cell migration correction (RCMC) in conditions of trigonometric function under square root in the range history and arc synthetic array in azimuth via reformatting the AA-BiSAR raw data. Besides presenting the proposed imaging approach, a complete resolution analysis of AA-BiSAR is given. Results of numerical simulation experiments on point targets validate the proposed imaging approach.

Response characteristics of gradient data from the frequency-domain controlled-source electromagnetic method

Studying how to improve the boundary recognition ability and resolution of anomalies is of great significance in the electromagnetic prospecting method. This paper analyzes the response characteristics of gradient data from the frequency-domain controlled-source electromagnetic method. A survey geometry that has one transmitter and many receiver locations, either along a line or over a grid, is used to obtain the electromagnetic field components. This kind of relatively dense coverage of receivers is needed in order to be able to determine the gradients. Spatial gradients in the two horizontal directions when measuring over a grid or in one horizontal direction when measuring along a line, and a frequency gradient which can give depth resolution, are considered in this paper. Forward modelling was carried out on a number of 3-D earth models to assess the capabilities and usefulness of the gradient data. The source–receiver geometry with survey lines arranged parallel to the direction of the grounded electric line source with measurements of the along-line component of the electric field, which is similar to the broadside geometry of marine CSEM, was found to be the best. The spatial gradients are able to indicate accurately the horizontal extents of the target, with the boundary identification ability of the spatial gradients being stronger than that of the original electromagnetic field components. Also, the frequency gradient is sensitive to the vertical extents of a target, with the main influence on the frequency gradient being the source–receiver distance, and the burial depth, resistivity and thickness of target. It is clear that the spatial and frequency gradients of electromagnetic data can provide a quick and reasonably accurate indication of the location and lateral extent of a conductivity anomaly in the subsurface, as well as an approximate depth and an indication of whether the anomaly is more or less conductive than the background.

Attractive passive direct positioning algorithm for localisation of multiple transmitters based on eigenvalue maximizing

In terms of the passive position determination problem, the most commonly used methods are based on two-step processing. While here, the authors propose a technique that estimates the locations of transmitters by processing the raw signals from all receivers at the central processor, which belongs to the direct position determination (DPD) concept. There are already efforts made on single target localisation through eigenvalue maximising based on the DPD technique. While the multi-target case encountered more commonly in realistic scenarios. By additionally combined with the image expansion algorithm, the sources can be extracted effectively and their positions are determined simultaneously. Simulation results illustrate that the localisation accuracy for each transmitter is equivalent to the two-step based approach at high signal-to-noise ratio (SNR). While for low SNR, the superiority and accuracy of the proposed method are also manifested.

WiFi Electromagnetic Field Modelling for Indoor Localization

Abstract The aim of this paper is to develop simplified model for WiFi electromagnetic field propagation. The model can be used in preliminary estimation of WiFi transmitter localization for the purpose of WiFi-based indoor localization. It can be particularly useful when designing structural networks.We have developed a simplified linear model of WiFi electromagnetic field modelling and compared it with the most commonly used, more sophisticated models and with measurement results which were carried out in the laboratory. As demonstrated by the results of measurements conducted using various hardware, the accuracy of this simplified model introduced is similar to the commonly used models, but the number of parameters is lower. Therefore, our model easier to implement in real life conditions. The model presented in this paper enables WiFi electromagnetic field modelling when the exact values of propagation parameters and transmitter characteristics is unknown. This is usually the case at the early stage of structural network design,when exact parameters of building construction materials are not known. As the model is very simple, it does not require much effort to deploy, while its accuracy is sufficient for preliminary WiFi transmitter localization. Simplified models of WiFi electromagnetic field propagation are known, but no comparative research combined with measurements has been done in this field. This paper provides a comparison of different electromagnetic field models which can be applied to WiFi electromagnetic field propagation together with measurement results.

Ionosphere Ray Tracing of Radio‐Frequency Signals and Solution Sensitivities to Model Parameters

AbstractMethods are developed to determine the refracted propagation paths of high‐frequency radio signals in the ionosphere and to determine the sensitivities of these paths to changes of the input model parameters. These techniques are being developed to support the assimilation of data from monostatic and multistatic ionosondes with the goal of improving parameterized estimates of ionosphere electron density profiles. An additional application area is that of navigation using signals from a ground‐based network of high‐frequency beacons. A nonlinear two‐point boundary value problem solver is developed using the shooting method with Newton updates. Robust convergence is achieved by seeding the algorithm with carefully designed first guesses of the wave vector's initial aiming angles and terminal group delay. Partial derivative sensitivities of the raypath solution are calculated using the adjoint of the two‐point boundary value problem. This approach speeds the calculations when the partial derivatives of many ionosphere model parameters need to be computed. The new algorithm has been applied successfully to determine the paths of O‐mode and X‐mode radio waves between known transmitter and receiver locations and to spitze reflection points. Spitze singularities pose no difficulties for the new algorithm because it uses a Hamiltonian raypath formulation that remains nonsingular at a spitze.

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar.

Transmitter and receiver position errors have been known to significantly deteriorate target localization accuracy in a multi-static passive radar (MPR) system. This paper explores the use of calibration targets, whose positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors. This paper firstly evaluates the Cramér–Rao lower bound (CRLB) for bistatic range (BR)-based target localization with calibration targets, which analytically indicates the potential of calibration targets in enhancing localization accuracy. After that, this paper proposes a novel closed-form solution, which includes two steps: calibration step and localization step. Firstly, the calibration step is devoted to refine the inaccurate transmitter and receiver locations using the BR measurements from the calibration targets, and then in the calibration step, the target localization can be accurately achieved by using the refined transmitter/receiver positions and the BR measurements from the unknown target. Theoretical analysis and simulation results indicate that the proposed method can attain the CRLB at moderate measurement noise level, and exhibits the superiority of localization accuracy over existing algorithms.

A hidden semi-Markov model for indoor radio source localization using received signal strength

Multipath propagation makes the use of received signal strength (RSS) unreliable as a signal propagation model for localization of a radio source based on RSS data. An approach to mitigation of this problem is the use of a Hidden Markov model (HMM) to represent the relationship between RSS and the radio source location by incorporating an environment prior and RSS source dynamics. The HMM structure forces a geometric form for the distribution for the sojourn time. This, combined with missing data problems, reduces confidence in location estimation. It is found, in this paper, that Hidden semi-Markov Models (HsMMs), with a more flexible sojourn time distribution are more able to represent source dynamics while retaining the advantages of HMMs for environmental constraints and improving resilience to missing measurements. The performance of the proposed HsMM algorithm is compared with a standard HMM via experiments and simulations involving indoor radio source localization using RSS data. Simulations use a ray tracing software-based simulator and the experiments for transmitter localization with RSS data are collected by software defined radios.

Completion Time Minimization With Path Planning for Fixed-Wing UAV Communications

Unmanned aerial vehicles (UAVs) have attracted increasing attention in wireless communications due to the high mobility. This paper investigates a fixed-wing UAV-to-UAV (U2U) communications system, with the aim of minimizing the information transmission time via proactively designing the UAV paths. First, we propose a general optimization framework for U2U communications, which covers the communication throughput requirement, interference from terrestrial transmitters, UAV maximum/minimum speeds and accelerations, and minimum U2U distance. To tackle the formulated optimization, the communication throughput constraint that contains uncertain locations of terrestrial transmitters is transformed into a deterministic expression with the aid of S-procedure, and the nonlinear equality constraints on the UAV paths are replaced by linear equality constraints with additional positive semidefinite matrix constraints. Then, we develop a path planning algorithm based on the exact penalty method and successive convex approximation. Furthermore, we design a heuristic path planning algorithm that solves the completion time minimization problem by iteratively addressing a series of throughput maximization problems. The proposed heuristic algorithm strikes a good tradeoff between the computational complexity and the achievable performance. Finally, the simulation results are presented to verify the proposed path planning algorithms under various parameter configurations.

Flexible method for improved transmitter parameter calibration in accurate large-scale positioning system

An accurate large-scale positioning system is a three-dimensional workspace measuring and positioning the laser scanning-based system that is widely used in smart manufacturing and assembly applications. The system includes laser transmitters that are typically calibrated using one of two methods: a high-precision rotary table-dependent method or a three-dimensional (3-D) coordinate control network-dependent method. However, these methods are error-prone and inefficient. We propose a flexible calibration method that is based on the transmitter geometry and employs the characteristic angles of the transmitter as calibration targets that do not change with transmitter location or orientation. The proposed method also utilizes a calibration algorithm that is based on a highly precise 3-D coordinate control network and includes an optimization algorithm and an estimation algorithm to produce initial values. The results of Monte Carlo simulations indicate that the proposed method enables the characteristic angles to maintain accuracy within 3 arc sec. Furthermore, the results of verification experiments show that the proposed method decreases the deviation of each control point and the root-mean-square error to 0.075 and 0.052 mm, respectively.

Innovations in Heart Rate Monitoring Devices and Smart Applications: Physical Configuration Matters!

Bluetooth/ANT+ heart rate monitors and smart device applications have the potential to advance heart rate monitoring in non-clinical settings. New innovative applications allow for heart rate monitoring of multiple users simultaneously; however, preliminary attempts to use a particular commercially available model in a typical university gymnasium setting revealed persistent issues with signal interruption; thus, the trustworthiness of the data was limited. PURPOSE: To reduce the prevalence of signal interruption by determining the best physical configuration of components. METHODS: A quasi-experimental repeated measures design was utilized to determine the best configuration of the system components. Cluster and ANOVA analyses determined good, better, and best configurations. The dependent variable was signal interruption and the unit of analyses was the number of signal interruptions per two-minute session. The independent variables were height (1.8m, 3.6m, and 5.4m), angle (60°, 75°, and 90°), and location (left corner, middle, right corner) of the transmitter component. University students, male and female adults ages 19-25 with no apparent health problems, were recruited to participate during undergraduate physical education teacher education lab classes. Participants were monitored while participating in physical activities during normal class sessions. Classes were conducted in a typical indoor gymnasium slightly larger than a single standard collegiate-sized basketball court. RESULTS: Inspection of the graphs and ANOVA analyses revealed that the best configuration of the system was transmitter device placement at a height of 1.8m’ F(2, 1,052) = 54.86, p < .001, partial η2 = .09, at a 60°angle F(2, 1,052) = 12.50, p < .001, partial η2 = .02, and in the left corner location F(2, 1,052) = 24.28, p < .001, partial η2 = .04. CONCLUSIONS: The height, angle, and location of the transmitter component all played a significant role in reducing the prevalence of signal interruption. It was determined that the best results were found with the lowest height and smallest angle chosen. Therefore, random placement of transmitter height, angle and location will not yield the best heart rate monitoring results.

QoS-Aware D2D Cellular Networks With Spatial Spectrum Sensing: A Stochastic Geometry View

Spectrum access and interference management are amongst the most challenging issues in device-to-device (D2D) cellular networks. In order to address these issues, this paper introduces spatial spectrum sensing (SSS) for D2D cellular networks to facilitate cellular spectrum sharing by D2D users while providing a quality of service guarantee for cellular users. In order to assess the performance of the proposed scheme, we adopt a stochastic geometry approach in which the locations of base stations and D2D devices are modeled as independent Poisson point processes (PPPs). Assuming that the locations of the active cellular transmitters form another independent PPP, we characterize the area spectral efficiency of D2D networks under cellular users’ outage probability constraint. The use of SSS prohibits D2D transmissions around the active cellular users because of which the locations of the active D2D transmitters are modeled as a Poisson hole process driven by the PPP of active cellular user locations. Our analysis carefully accounts for this spatial separation between active cellular users and active D2D devices. Extensive simulation and numerical results are presented to verify our analysis and demonstrate the advantages of SSS-based D2D cellular networks.