Signal Strength Measurements Research Articles

Training-Free Artifact Detection Method for Radio Tomographic Imaging Based Device-Free Localization

Radio tomographic imaging (RTI) is a promising device-free localization (DFL) method by reconstructing an attenuation image from the variations of received signal strength (RSS) measurements. Targets are considered to be at positions of some pixels with local maximums in the attenuation image. However, the number of local maximums generally exceeds the number of real targets, which will lead to large localization errors. The local maximum which does not have its corresponding real target is defined as an “artifact”. Through our analysis, two causes for artifacts are concluded: 1) multi-path interference: RSS measurements for links that are far from the targets may have variations due to multi-path interference, even though these links are not blocked by the targets. 2) intersecting affected links: the affected links blocked by different targets may intersect within the monitoring area, fabricating artifacts. At a position of artifact, there seems to be a target whose interference effect on links is similar to that of a real target. The quality of the attenuation image will deteriorate because of the above two inevitable influencing factors. To alleviate the effect of artifacts, a training-free artifact detection method is proposed. We formulate the artifact detection problem in the attenuation image as a multi-component optimization problem combing the information of feature links and the density of intersection points. The alternating direction method of multipliers (ADMM) is used to derive a closed-form solution. Experiments are conducted to validate the advantages of the proposed artifact detection method.

Heading Estimation Using Ultra-Wideband Received Signal Strength and Gaussian Processes

It is essential that a robot has the ability to determine its position and orientation to execute tasks autonomously. Heading estimation is especially challenging in indoor environments where magnetic distortions make magnetometer-based heading estimation difficult. Ultra-wideband (UWB) transceivers are common in indoor localization problems. This letter experimentally demonstrates how to use UWB range and received signal strength (RSS) measurements to estimate robot heading. The RSS of a UWB antenna varies with its orientation. As such, a Gaussian process (GP) is used to learn a data-driven relationship from UWB range and RSS inputs to orientation outputs. Combined with a gyroscope in an invariant extended Kalman filter, this realizes a heading estimation method that uses only UWB and gyroscope measurements.

Cooperative Three-Dimensional Position Mapping Based on Received Signal Strength Measurements: Algorithm Design and Field Test

This paper presents a new approach to accurately and efficiently identifying a large number of wireless devices blindly installed to known three-dimensional installation/fitting points, based on received signal strengths (RSSs) between the devices. The approach is non-trivial because of the factorial, mapping nature of the considered problem, the multiplicative ranging errors of the RSS measurements (with standard deviation of 5–7 dB), and the requirement of high mapping accuracy in many internet-of-things (IoT) applications, e.g., industrial IoT and aircraft. The consideration of a structured environment where the set of candidate node positions is known beforehand shifts the problem of interest from a pure position estimation problem to a position assignment problem. The key idea of the proposed approach is that we interpret the position mapping problem with a probabilistic graphical model, where the factorial nature of mapping (more specifically, the mutual exclusiveness of devices at every installation point) is fully captured. A max-product belief propagation is designed against the probabilistic graph, to estimate the max-marginal position distribution of each device. The Kuhn-Munkres algorithm is applied to preserve the mutual exclusiveness of devices throughout the belief propagation and to decide device locations based on the estimated position distributions. Large-scale simulations and field tests are carried out, showing that the new approach achieves close-to-100% accuracy in simulations with hundreds of blindfolded devices under RSS measurement errors with standard deviation of 5–7 dB. Our approach also achieves 100% accuracy in all field trials with 76 devices inside the cabin of a Fokker 100 airplane, dramatically outperforming baseline techniques.

Research on the Minimum Size of Received Signal Strength Difference Localization Network

The received signal strength difference (RSSD) localization is a kind of method to locate emission sources by measuring the differences of received signal strength level between the monitoring stations and is essentially the truth value ratios of measured signal strength. In the existing literatures, only the rule of RSSD localization circle of two monitoring stations and the geometric relation of RSSD localization circle of five monitoring stations were analyzed, but the number and the station layout of the minimum RSSD localization network have not been investigated. In the present work, first, based on the existing RSSD localization equation, the constants of the commonly used wave propagation models are provided. Then, the minimum RSSD localization network is proved through algebraic analysis, which is that four monitoring stations not distributed on a straight line can locate the signal source at one point. The relationship between the localization accuracy and the signal strength error of the RSSD location network with different scales is studied further and formulated as a nonlinear programming optimization problem. It is found that the localization stability of the network with four stations is poor, and there is a serious localization deviation outlier phenomenon. Therefore, the network with four stations is not available for radio monitoring networks with a signal strength error of ± 5 to ± 10 dB. The RSSD network with five stations is basically the minimum available size, and the RSSD network with nine stations can approach the localization accuracy of the angle of arrival (AOA) network with three stations.

Are global forests performing in sync? The need to account for spatiotemporal biases in tree‐ring records

AbstractPopulations whose dynamics are driven by correlated environmental stochasticity face increased risk of extinction. Forests in particular are being pushed to their physiological limits under global change; hence, the analysis of common patterns of tree performance across scales becomes crucial to discern early warning signals and tipping points. Here, we critically evaluate customary and recent approaches for the analysis of time series of radial growth based on simple correlations as measure of direction and signal strength shared by spatially segregated forests (synchrony). By accounting for changes in spatial distribution of populations and temporal coverage of tree‐ring records, we show that growth synchrony has not substantially augmented for the past 150 years across Europe, a continent with high availability of tree‐ring series. We guard against the use of absolute correlations as a metric of synchrony and stress that robust analytical methods should be applied to evaluate synchrony trends when using biased spatiotemporal databases.

Real-Time Tracking System Based on RFID to Prevent Worker–Vehicle Accidents

In this letter, a radio frequency identification (RFID)-based location and tracking system that uses receiver signal strength (RSS) measurements is presented. The system is intended to be deployed at industrial scenarios or warehouses involving heavy machinery and vehicles in motion such as forklifts, and/or low visibility areas, aiming at preventing accidental collisions with workers. For this purpose, RFID tags are attached to helmets of the workers. The UHF reader antennas are located in the vicinity of the area where the workers are creating a coverage area where workers close to the vehicle can be detected and tracked. To deal with the propagation effects that degrade the RSS values, a propagation model based on on-site measurements together with an accurate characterization of the radiation pattern of the RFID reader antennas has been proposed. Validation with measurements in an scenario resembling the industrial environment is presented.

Practical Privacy-Preserving Indoor Localization Based on Secure Two-Party Computation

We present a privacy-preserving indoor localization scheme based on received signal strength measurements, e.g., from WiFi access points. Our scheme preserves the privacy of both the client's location and the service provider's database by using secure two-party computation instantiated with known cryptographic primitives, namely, Paillier encryption and garbled circuits. We describe a number of optimizations that reduce the computation and communication overheads of the scheme and provide theoretical evaluations of these overheads. We also demonstrate the feasibility of the scheme by developing a proof-of-concept implementation for Android smartphones and commodity servers. This implementation allows us to validate the practical performance of our scheme and to show that it is feasible for practical use in certain types of indoor localization applications.

Interference Alignment Inspired Opportunistic Communications in Multi-Cluster MIMO Networks with Wireless Power Transfer

In this work, we jointly investigate the issues of node scheduling and transceiver design in a sensor network with multiple clusters, which is endowed with simultaneous wireless information and power transfer. In each cluster of the observed network, S out of N nodes are picked, each of which is capable of performing information transmission (IT) via uplink communications. As for the remaining idle nodes, they can harvest energy from radio-frequency signals around their ambient wireless environments. Aiming to boost the intra-cluster performance, we advocate an interference alignment enabled opportunistic communication (IAOC) scheme. This scheme can yield better tradeoffs between IT and wireless power transfer (WPT). With the aid of IAOC scheme, the signal projected onto the direction of the receive combining vector is adopted as the accurate measurement of effective signal strength, and then the high-efficiency scheduling metric for each node can be accordingly obtained. Additionally, an algorithm, based on alternative optimization and dedicated for transceiver design, is also put forward, which is able to promote the achievable sum rate performance as well as the total harvested power. Our simulation results verify the effectiveness of the designed IAOC scheme in terms of improving the performance of IT and WPT in multi-cluster scenarios.

Endpoint PCR coupled with capillary electrophoresis (celPCR) provides sensitive and quantitative measures of environmental DNA in singleplex and multiplex reactions.

The use of sensitive methods is key for the detection of target taxa from trace amounts of environmental DNA (eDNA) in a sample. In this context, digital PCR (dPCR) enables direct quantification and is commonly perceived as more sensitive than endpoint PCR. However, endpoint PCR coupled with capillary electrophoresis (celPCR) potentially embodies a viable alternative as it quantitatively measures signal strength after PCR in Relative Fluorescence Units (RFU). Provided comparable levels of sensitivity are reached, celPCR permits the development of cost-efficient multiplex reactions, enabling the simultaneous detection of several target taxa. Here, we compared the sensitivity of singleplex and multiplex celPCR to dPCR for species-specific primer pairs amplifying mitochondrial DNA (COI) of fish species occurring in European freshwaters by analyzing dilution series of tissue extracts as well as field-collected water samples. Both singleplex and multiplex celPCR and dPCR displayed comparable sensitivity with reliable positive amplifications starting at two to 10 target DNA copies per μl extract. celPCR was suitable for quantifying target DNA and direct inference of copy numbers from RFU was possible after accounting for primer effects in linear mixed-effects models and calibration via dPCR. Furthermore, multiplex celPCR and dPCR were successfully used for the detection and quantification of fish-eDNA in field-collected water samples, confirming the results of the dilution series experiment and exemplifying the high sensitivity of the two approaches. The possibility of detection and quantification via multiplex celPCR is appealing for the cost-efficient screening of high sample numbers. The present results confirm the sensitivity of this approach thus enabling its application for future eDNA-based monitoring efforts.

Received Signal Strength Fingerprinting-Based Indoor Location Estimation Employing Machine Learning.

The fingerprinting technique is a popular approach to reveal location of persons, instruments or devices in an indoor environment. Typically based on signal strength measurement, a power level map is created first in the learning phase to align with measured values in the inference. Second, the location is determined by taking the point for which the recorded received power level is closest to the power level actually measured. The biggest limit of this technique is the reliability of power measurements, which may lack accuracy in many wireless systems. To this end, this work extends the power level measurement by using multiple anchors and multiple radio channels and, consequently, considers different approaches to aligning the actual measurements with the recorded values. The dataset is available online. This article focuses on the very popular radio technology Bluetooth Low Energy to explore the possible improvement of the system accuracy through different machine learning approaches. It shows how the accuracy–complexity trade-off influences the possible candidate algorithms on an example of three-channel Bluetooth received signal strength based fingerprinting in a one dimensional environment with four static anchors and in a two dimensional environment with the same set of anchors. We provide a literature survey to identify the machine learning algorithms applied in the literature to show that the studies available can not be compared directly. Then, we implement and analyze the performance of four most popular supervised learning techniques, namely k Nearest Neighbors, Support Vector Machines, Random Forest, and Artificial Neural Network. In our scenario, the most promising machine learning technique being the Random Forest with classification accuracy over 99%.

Capacities of TEC measurements by the low-cost GNSS receiver based on the u-blox ZED-F9P for ionospheric research

A prototype of a low-cost GNSS receiver assembled on base of the u-blox ZED-F9P module is described in the paper. The original low-cost GNSS receiver (OGNSS-R) allows made the parallel registration of 184 channels in the entire frequency range (1176 ÷ 1610 MHz) of the main GNSS (GPS, GLONASS, Galileo, Beidou) and recording raw data of carrier-phase, pseudorange (code) and signal strength measurements. The obtained data processing allows to calculate the slant total electron content (TEC), TEC variations and other most popular TEC-based indices of ionospheric activity. The comparative studies of these parameters and similar parameters obtained by simultaneous measurements on the professional geodetic GNSS receiver Trimble Alloy (KZN2 station of the IGS network) were preformed. The analysis showed the median value of the signal strength at the L1 frequency for the KZN2 station are 8% higher than that at the low-cost GNSS receiver based on the u-blox ZED-F9P module (KZN2–48.75 dBHz; OGNSS-R – 45dBHz). For the L2 frequency that difference is less than 2% (KZN2–49.4 dBHz; OGNSS-R – 48.5 dBHz). The median levels of relative slant TEC and TEC-based indexes of the ionospheric activity obtained by the Trimble Alloy receiver at KZN2 station are 25÷50% lower than for the u-blox ZED-F9P receiver. Thus, the using of starter kits such as the simpleRTK2b debug board based on the u-blox ZED-F9P module described in the paper, is really actual for creating a permanent network of GNSS-stations and/or for carrying out field measurements in experimental campaigns.

Wireless Optimization Algorithm for Multi-floor AP deployment using binary particle swarm optimization (BPSO)

Optimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal thresholds, and Received Signal Strength (RSS) measurements simulated with Wireless Insite (WI) software were considered to work in conjunction with the proposed optimization algorithm. Additionally, the AP deployment results obtained from WI and optimization will be compared with the simulation results of the current AP diffusion within the target building. These comparisons will be based on the most important RSS parameters, path loss (PL) and interference. The comparison results showed a significant improvement in RSS and path loss values of (-11.55) dBm and (11.55) dBm. While the interferences are decreased by (7.87 %). Furthermore, the result of performance analysis showed that the proposed algorithm outperforms the current AP deployment by 39.23% in coverage ratio.

Assessment and Development of Path Loss Propagation Model for Ikire Metropolis, Nigeria

The aim of this paper is to assess and develop path loss propagation model for terrestial radio broadcasting station in Ikire, Nigeria. In carrying out the study, the reception quality of Osun State Corporation (OSBC) broadcast signal strength within Ikire metropolis in Irewole Local Government Area of Osun State, Nigeria was assessed using BC1173 Field Strength meter. The data obtained from the signal strength measurements around the metropolis were subsequently analysed and used for the development of an ideal propagation path loss model for the metropolis. The developed path loss model for the metropolis was evaluated and found to outperform the COST-231 Hata model in literature. The comparative performance evaluation result of the developed model and the COST-231 Hata model buttresses the need for developing different path loss models for different radio signals in different locations under different environmental factors. In addition, the finding of the study establishes a standard propagation path loss model that can be used for planning and designing efficient wireless communication link for terrestrial radio broadcasting station in the metropolis and any other environments with similar environmental factors.

3D shooting and bouncing ray approach using an artificial intelligence-based acceleration technique for radio propagation prediction in indoor environments

The shooting and bouncing ray approach is an important method used in ray-tracing simulations to estimate the propagation of radio waves. However, in this method, unnecessary rays, which are useless for follow-up and consume a large amount of simulation resources, may emerge. This study proposes an artificial intelligence-based acceleration solution, unlike geometry-based approaches in the literature. The proposed approach focuses on ray characteristics, not ambient geometry. An analysis of ray characteristics is carried out by trained simulation-decision engines at run-time. The decision engine training was carried out with datasets obtained from traditional shooting and bouncing simulations that use different parameters. The success of the proposed method was tested for three different real environments containing line-of-sight and non-line-of-sight receiver points, where the received signal strength measurements had been made earlier. For better training and more detailed analysis, a total of 63 simulations using different parameters were made in both training data and test simulations. The obtained results show the success of the proposed method.

An efficient clustering with robust outlier mitigation for Wi-Fi fingerprint based indoor positioning

Wi-Fi fingerprint systems provide cost-effective and reliable solution for indoor positioning. However, such systems incur high calibration cost in the training phase and high searching overhead in the positioning phase. Moreover, huge storage requirement for the radio map of a large-scale fingerprint system is another major issue. Several solutions based on crowd-sourcing or machine learning technique have been proposed in literature to reduce the calibration overhead. On the other hand, various clustering methods have been proposed over the past decade to reduce the searching overhead. However, none of the existing systems has addressed the issue of high storage requirement for the fingerprint database constructed in the training phase. Moreover, presence of outlier in the received signal strength (RSS) measurements severely impacts the positioning accuracy of such systems. Thus, this paper proposes an efficient clustering strategy for fingerprint based positioning systems to reduce the storage overhead and searching overhead incurred by such systems and also proposes a robustoutlier mitigation technique to improve their positioning accuracy. The performances of our proposed positioning system are evaluated and compared with five existing fingerprint techniques in both the simulation test bed as well as real indoor environment via extensive experimentation. The experimental results demonstrate that our proposed system can not only reduce the storage overhead and searching overhead but also improve the positioning accuracy compared to the other existing techniques.

Effect of noise, partial synchronization, and sampling frequency inaccuracies on amplitude measurement of multiple linear chirp signals

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.

Installation of Handphone Signal Booster Antennas at 900 MHz Frequency in Onggari Village Merauke Regency

The importance of cellular communication demands to improve the quality of good and quality services in all regions including rural areas. The limitations of BTS signal propagation in Kumbe village have disrupted cellular communication services in Onggari village. By using the Yagi antenna 13 elements as a cellular signal amplifier that is modified by using a repeater so that the handphone signal can be accessed at a greater distance from the BTS location. The results obtained after mounting the signal amplifier antenna is very good where the signal increase is at 4 Barr, the signal strength is -75 dBm at a distance of 1 meter with “excellent” sound quality, while the results of the measurement of signal strength and signal quality for sunny weather are better than when it rains.

Traffic collision avoidance system: false injection viability

Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded access to a physical TCAS unit; instead, this research creates a novel program, TCAS-False Injection Environment (TCAS-FIE), that incorporates real-world distributed computing systems to simulate a ground-based attacker scenario which explores how a false injection attack could target an operational aircraft. TCAS-FIEs’ simulation models are defined by parameters to execute tests that mimic real-world TCAS units during Mode S message processing. TCAS-FIE simulations execute tests over applicable ranges (5–30 miles), altitudes (25–45K ft), and bearings standard for real-world TCAS tracking. The comprehensive tests compare altitude, measure range closure rate, and measure signal strength from another aircraft to determine the delta in bearings over time. In the attack scenario, the ground-based adversary falsely injects a spoofed aircraft with characteristics matching a Boeing 737-800 aircraft, targeting an operational Boeing 737-800 aircraft. TCAS-FIE completes 555,000 simulations using the various ranges, altitudes, and bearings. The simulated success rate to trigger a resolution advisory is 32.63%, representing 181,099 successful resolution advisory triggers out of 555,000 total simulations. The results from additional analysis determine the required ranges, altitudes, and bearing parameters to trigger future resolution advisories, yielding a predictive threat map for aircraft false injection attacks. The resulting map provides situational awareness to pilots in the event of a real-world TCAS anomaly.

RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution needs to be employed. The accuracy of this model depends strongly on the atmospheric turbulence strength which causes the scintillation effect. To this end, a variety of probability density functions were utilized to model the optical channel according to the strength of the refractive index structure parameter. Although many theoretical models have shown satisfactory performance, in reality they can significantly differ. This work employs an information theoretic method, namely the so-called Jensen–Shannon divergence, a symmetrization of the Kullback–Leibler divergence, to measure the similarity between different probability distributions. In doing so, a large experimental dataset of received signal strength measurements from a real FSO link is utilized. Additionally, the Pearson family of continuous probability distributions is also employed to determine the best fit according to the mean, standard deviation, skewness and kurtosis of the modeled data.

The anomalous production of multi-leptons and its impact on the measurement of Wh production at the LHC

Anomalies in multi-lepton final states at the Large Hadron Collider (LHC) have been reported in Refs. (von Buddenbrock et al., J Phys G 45(11):115003, arXiv:1711.07874 [hep-ph], 2018; Buddenbrock et al., JHEP 1910:157, arXiv:1901.05300 [hep-ph], 2019). These can be interpreted in terms of the production of a heavy boson, H, decaying into a standard model (SM) Higgs boson, h, and a singlet scalar, S, which is treated as a SM Higgs-like boson. This process would naturally affect the measurement of the Wh signal strength at the LHC, where h is produced in association with leptons and di-jets. Here, h would be produced with lower transverse momentum, p_{Th}, compared to SM processes. Corners of the phase-space are fixed according to the model parameters derived in Refs. (von Buddenbrock et al., J Phys G 45(11):115003, arXiv:1711.07874 [hep-ph], 2018; von Buddenbrock et al., Eur Phys J C 76(10):580, arXiv:1606.01674 [hep-ph], 2016) without additional tuning, thus nullifying potential look-else-where effects or selection biases. Provided that no stringent requirements are made on p_{Th} or related observables, the signal strength of Wh is mu (Wh)=2.41 pm 0.37. This corresponds to a deviation from the SM of 3.8sigma . This result further strengthens the need to measure with precision the SM Higgs boson couplings in e^+e^-, and e^-p collisions, in addition to pp collisions.