Radio Signals Research Articles

Fingerprint localisation for fine‐scale wildlife tracking using automated radio telemetry

Abstract Automated radio telemetry systems are one of the most widely applicable methods for tracking wildlife at fine spatiotemporal scales. A growing trend is for these systems to apply large networks of receivers to detect radio signal strength (RSS) from radio‐tagged individuals. Analytical methods to derive position estimates using RSS localisation, however, are relatively underdeveloped in the field of wildlife tracking. Here, we apply approaches from indoor positioning systems to develop a new method, radio fingerprinting, for localising radio‐tagged animals in structurally complex, outdoor environments. This method characterises the RSS patterns at known locations to generate a radio map of the study area, which is then used to predict the location of new RSS patterns. We conducted field tests to evaluate the localisation accuracy of radio fingerprinting relative to multilateration, a commonly used method for RSS localisation. To do so, we established an experimental receiver network covering multiple habitat types and compared the localisation accuracy of radio fingerprinting to multilateration. Additionally, we evaluated how a variety of features characteristic of typical tracking data sets affected the accuracy of both methods. While both methods had a similar median error under ideal conditions (~30 m), radio fingerprint localisation method offered several advantages over multilateration. Multilateration localisation estimates were highly affected by missed detections from the nearest receiver to the test point, which occurred in 30% of cases. In these cases, the median error was 103 m, over a 3.5‐fold increase. Distance to the nearest receiver also biased multilateration estimates with error increasing as the distance increased. Additionally, errors from multilateration estimates were higher in more densely vegetated areas. In contrast, fingerprinting position estimates were largely robust to each of these scenarios. Automated radio telemetry enables the fine‐scale, continuous tracking of range‐resident animals. We present radio fingerprinting as a localisation method in outdoor environments where standard localisation methods are error‐prone due to habitat heterogeneity and missed detections. This approach can be applied to any automated radio telemetry hardware and to any study system where a radio map can be generated.

Optimization of aero-engine condition monitoring by autoregressive model analysis based on wireless communication

The high value of aero-engines makes it necessary to extend their life in terms of econ-omy of use. Health management is an important basis for this work. Background: The vibration signal is an important representation of the working state of an aero-engine. The current usual method is based on wired communication with simple waveform presentation. The many incon-veniences of this method have seriously affected the further development of this work. Methods: This research team acquires engine vibration signals in real time through a designed wireless signal sensor, and then analyzes and visualizes the signals in depth. Results: Through this method, it can visually and effectively demonstrate signal characteristics for engineers, effectively identify fault signals, and monitor engine operating conditions in real time. Conclusions: The method enables the optimization of aero-engine work-state monitoring.

Globally convergent path-aware optimization with mobile robots

Consider a mobile robot that must navigate as quickly as possible to the global maxima of a function (e.g. density of seabed litter, pollutant concentration, wireless signal strength) defined over its operating area. This objective function is initially unknown and is assumed to be Lipschitz continuous. The limited velocity of the robot restricts the next samples to neighboring positions, and to avoid wasting time and energy, the robot’s path must be adapted as new information becomes available. The paper proposes two methods that use an upper bound on the objective to iteratively change the position targeted by the robot as new samples are acquired. The first method is FTW, which Turns When the best value seen so far of the objective Function is larger than the bound of the current target position. The second is FTWD, an extension of FTW that takes into account the Distance to the target. Convergence guarantees are provided for both methods, and a convergence rate is proven to characterize how fast the FTW suboptimality decreases as the number of samples grows. In a numerical study, FTWD greatly improves performance compared to FTW, outperforms two representative source-seeking baselines, and obtains results similar to a much more computationally intensive method that does not guarantee convergence. The relationship between FTW and FTWD is also confirmed in real-robot experiments, where a TurtleBot3 seeks the darkest point on a 2D grayscale map.

Optimal filtering of an information process depended on noninformative parameters described by Marcovian chain when radio signals are receiving

In radio navigation and radio location tasks tracking systems on radio signals parameters often operate when object acceleration has stepwise changing. If we synthesize various tracking systems using optimal filtering theory it is necessary to represent the estimated process as a multidimensional Marcovian process. But such representation for stepwise changed acceleration is a rough approximation that lead to estimates accuracy degradation. One of possible approach to such disambiguation is to describe acceleration as Marcovian chain with finite number of states. This approach is developed in the article. Objective. To synthesize an optimal filtering algorithm of information process depended on noninformative parameters described by Marcovian chain using the observation grouping method when receiving radio signals and to implement simulation for an illustrative task.

Quasi-likelihood estimation of the arrival time of an ultra-wideband quasi-radio signal with unknown amplitude and initial phase

The problem of estimating the time of arrival of a signal is relevant in the fields of radio and hydrolocation, radio astronomy, remote observation and sensing, etc. The useful signal is often described by a quasi-deterministic function of time, which can be regular or discontinuous. In recent years, problems of processing ultra-wideband signals have been of significant interest. Among the many UWB signals, it is customary to distinguish a separate class of ultra-wideband quasi-radio signals, the structure of which is similar to the structure of narrowband radio signals, but the condition of relative narrowband for which may not be met. Algorithms for estimating the arrival time of regular ultra-wideband quasi-radio signals have been studied in the existing literature. In this case, the synthesis and analysis of an algorithm for quasi-plausible estimation of the arrival time of a discontinuous signal of finite duration and arbitrary shape is of practical interest. The purpose of the work is to synthesize and analyze a quasi-likelihood algorithm for estimating the time of arrival of a discontinuous ultra-wideband quasi-radio signal with an unknown amplitude and initial phase against a background of white Gaussian noise. In this work, closed asymptotically exact expressions for the bias and scattering of the estimate are obtained, which make it possible to study the effectiveness of the synthesized algorithm, as well as compare its effectiveness with special cases of signal models - narrowband and wideband radio and video signals. The results of the study make it possible to determine losses in the accuracy of estimation the signal arrival time due to a priori ignorance of the initial phase and shape of the modulating function of the signal. Depending on the required accuracy of estimate the time of arrival of an ultra-wideband quasi-radio signal, it is possible to optimize the parameters of the transmitted signals and determine the limits of applicability of the designed radio system.

Synthesis and analysis of an ensemble of SAR signals

Due to the development of digital technologies for receiving and transmitting radio location signals, the development of modern radars with a synthesized aperture has made it possible to widely use an ensemble of probing signals with periodic sequences of identical pulses. The manipulation of probing pulses in transmission opens up opportunities to reduce the level of interference of ambiguity in range, expand the capture bands, improve azimuth resolution, and reduce interference from the background surrounding the target. However, the literature currently does not sufficiently address the issues of synthesis and analysis of ensembles of probing signals for a synthetic aperture radar (RSA) placed on board an unmanned aerial vehicle. Several variants of the implementation of ensembles of probing signals in the RSA are considered, mathematical modeling and experimental testing are carried out on the basis of the RSA operating in the VHF frequency range, placed on board an unmanned aerial vehicle (UAV). The conducted modeling allows us to draw the following conclusions. The best characteristics are possessed by an ensemble of signals encoded by Huffman codes, where M-sequences were used to "scatter" the roots. In second place is an ensemble of signals encoded by composite M-sequences. However, with an increase in the base of probing signals (N>64), the best results are shown by an ensemble of signals based on composite M-sequences.

Computer vision quickly identifies radio signals with unlimited accuracy

A seminal component of systems thinking is the application of an advanced technology in one domain to solve a challenging problem in a different domain. This article introduces a method of using advanced computer vision to solve the challenging signal processing problem of specific emitter identification. A one-dimensional signal is sampled; those samples are transformed into to two-dimensional images by computing a bispectrum; those images are evaluated using advanced computer vision; and the results are statistically combined until any user-selected level of classification accuracy is obtained. In testing on a published DARPA challenge dataset, for every eight additional signal samples taken from a candidate signal (out of many thousands), classification error decreases by an entire order of magnitude.

Determination of the resolution intervals in time and frequency under the influence of multiplicative noise based on the Woodworth criterion

Issues related to estimating the influence of quasi-deterministic and fluctuating multiplicative noise on the delay resolution and frequency resolution of systems processing radio signals based on the Woodward criterion for narrow-band and broadband signals are considered. The problem of resolution when detecting or measuring signal parameters can be considered both for useful signals alone and for cases when interfering signals are present as well. It is pointed out that the effect of multiplicative noise on the signal almost always leads to a resolution problem. It is shown, that under the influence of significant broadband multiplicative noise, the time resolution interval is determined only by the signal envelope and does not depend on its phase structure. For instance, for signals with a rectangular or bell-shaped envelope, it is equal to the equivalent signal duration. Examples of calculating resolution intervals under the influence of multiplicative noise are given. Taking into account the effect of multiplicative noise on signal resolution leads to an increase in the efficiency of radio systems, detection of objects being an example.

Heart Rate Variability Estimation based on RFID Tag-Pair in Dynamic Environments

With the rapid development of smart healthcare, accurate Heart Rate Variability (HRV) estimation for the early detection of diseases has become a hot research topic. Advanced work uses the wireless signal to estimate the heartbeat in a contact-free way, which usually cannot separate multiple users or work in a dynamic environment. In this paper, we propose a lightweight heartbeat-sensing method based on RFID tag pairs, which focuses on HRV extraction in a more general sensing scenario. Based on the tag-pair design, we build a novel heartbeat and respiration model to describe the signal relationship between the two tags from the time and space domains. Based on the model, we propose a Calibrated Temporal-Spatial IQ-Shaping-based signal cancellation algorithm to cancel the respiration and extract the heartbeat. To remove the interference in dynamic measurement, we build an IQ-based signal model via a Principal Component Analysis-based interference estimation. To reduce the statistical error in HRV extraction, we further design a neural network to predict the HRV index. We have implemented a system prototype in a real environment with COTS RFID devices. Extensive experiments show that our system can achieve a median RMSSD error of 7.51ms, which satisfies the medical demand in HRV measurement.

A microfluidic patch for wireless wearable electrochemical detection of sweat metabolites

Wearable sweat sensors provide an innovative detection method for analyzing human physiological and biochemical parameters and play an important role in detecting the potential risks of chronic diseases. Existing commercial wearable sensors (Apple iWatch, HUAWEI smart band) have problems such as single detection index (heart rate or blood pressure), and mainly focus on the physical information. This work studied an integrated microfluidic patch to simultaneously detect several biomarkers (pH, sodium ions, and uric acid) in sweat. We achieved the detection of pH level, sodium, and uric acid in linear ranges of 4–8, 0–160 mM, and 5–160 μM, respectively, covering well the clinically relevant ranges in the healthy human sweat. Laser engraving was chosen to prepare a microfluidic layer, and the sweat collection function was realized by combining hydrophilic and hydrophobic microfluidic synergy. It could efficiently collect the required sweat sample volume (80 μL) within 30 s while avoiding the contamination caused by directly contact with the skin. In addition, a wireless signal acquisition and transmission system was designed with the signal reading, processing, and wireless transmission functions, which can display the testing results in real time on Android phone-specific application software. We combined the wireless system with a microfluidic patch for on-body testing to verify the good wearability of the sweat sensor. This research realized the wireless data processing and transmission while improving sweat collection efficiency. In addition, it could detect various sweat physiological components in real-time, and provides a multiparameter, real-time, and portable sensing platform.

A Battery‐Free Wireless Tactile Sensor for Multimodal Force Perception

AbstractMultimodal tactile sensors, as key information input channel in human‐machine interactions, have faced the significant challenges including high power‐consumption, multimodal data fusion, and wireless transmission. In this work, a battery‐free multimodal wireless tactile sensor (TC‐MWTS) based on tribo‐capacitive coupled effect for normal and shear force fusion sensing is proposed, which is enabled by a 3D structure combining a triboelectric sensor and a capacitive sensor coupled with an inductive coil. A triboelectric sensor equipped with contact‐discharge structures exhibits 25‐fold wireless signal enhancement compared to conventional triboelectric sensors. Based on the characteristics of dual time‐frequency domain information existing in the wireless signals, both normal and shear forces can simultaneously be converted into voltage amplitude V and eigenfrequency f, respectively, without crosstalk and complex decoupling signals. The TC‐MWTS exhibits a maximum sensitivity of 2.47 V kPa−1 for normal force from 2 to 30 kPa and a sensitivity of 0.28 MHz N−1 for shear force between 0.3 and 1.0 N. Finally, the excellent sensing capability of TC‐MWTS to sense complex multidimensional forces in human‐machine interaction is demonstrated. This work innovatively proposes a new mechanism and methodology for effectively fusing and processing multimodal tactile information, which may drive the tremendous development of low‐power multimodal tactile sensing system.

Improving Radio Signal from Baghdad University Radio Telescope Using the Savitzky-Golay Filter

Astronomical radio observations from a small radio telescope suffer from various types of noise. Hence, astronomers continuously search for new techniques to eliminate or reduce such noise and obtain more accurate results. This research investigates the impact of implementing the Savitzky-Golay filter on enhancing radio observation signals retrieved from the Baghdad University Radio Telescope (BURT). Observations from BURT were carried out for different Galactic coordinates, and then a MATLAB code was written and used to implement the Savitzky-Golay filter for the collected data. This process provides an assessment of the ability of the filter to reduce noise and improve the quality of the signal. The results of this research clearly showed that applying the Savitzky-Golay filter reduces the noise and enhances the signal of astronomical radio observations. However, the filter should be used appropriately to preserve the original features of the signal. In conclusion, the filter is considered an efficient tool for enhancing the radio signal by reducing the noise and smoothing the signal. Therefore, the filter provides a substantial contribution and improvement to the field of radio astronomy.

Full-duplex two-way no-relay cross-media communication method based on acoustic wave conversion

Abstract Due to the difference in acoustic impedance between water and air, the water interface becomes a natural barrier. Underwater sound waves will bounce when they propagate to the water surface. Electromagnetic waves and light waves in the air will rapidly attenuate after passing through the water surface and going underwater, making it difficult to complete air-water cross-media information transmission. In this article, we first analyze the theoretical characteristics and vibration model of the water surface after medium collision, and develop a new full-duplex communication method across the air-ocean medium, which does not rely on relay equipment and only uses three transmission media in the air. Propagate signals in the sea channel physical field to achieve two-way communication, using the mutual conversion between laser, acoustic, and radio frequency signals to fill the gap in cross-media communication technology that can simultaneously achieve two-way, full-duplex and non-relay. It has been verified through experimental installations carried out in laboratory water tanks and large comprehensive anechoic pools that it is able to achieve full-duplex communication links across the air-sea surface, indicating that the combination of laser acousticization and radio frequency-acoustic wave conversion can be used across medium full-duplex wireless communication provides a feasible method for communication that breaks through the water interface.

Study of Nuclear Magnetic Resonance at Engineering and Medical Universities

The relevance of this study is related to the breadth of the nuclear magnetic resonance (NMR) method application in modern engineering and medical technologies. The purpose of the work is to adapt the material using the NMR method for students of medical, engineering and socio-humanitarian specialties and areas of study at different levels of presentation. The novelty of the research is as follows: the elements of knowledge for explaining the NMR method are highlighted; three levels of NMR explanation are justified and defined – classical and two quantum (qualitative and quantitative). The following methods have been used in the work: analysis and generalization of scientific, educational and methodological literature (on the content of the NMR method, nuclear spectroscopy and magnetic resonance imaging, the main professional educational programs of specialties and areas of study for undergraduate and graduate students of engineering and medical universities); designing the content of educational material; designing teaching methods and methods. Specific results include the development of three levels of NMR study. The classical level is based on the concepts of the magnetic induction vector of a circular current and its rotation around the magnetic induction of a constant magnetic field with a certain frequency, resonant absorption of radio signal energy by the core when their frequencies coincide. Quantum levels of study operate with the concepts of the orbital and magnetic spins of the atomic nucleus, the gyromagnetic ratio, Larmor precession, splitting of the energy levels of the atomic nucleus, the Bohr magnetone, and resonant absorption of energy by the nucleus. The classical level is recommended for students of social and humanitarian fields who do not study pure physics. The quantum qualitative level is recommended for students of specialties and fields of study at medical and engineering universities who do not study quantum physics as a special discipline. For students of engineering specialties related to quantum technologies, and medical specialties “Pharmacy” and “Dentistry”, undergraduates studying medical technology, a quantum quantitative level is recommended. The material of this study is of practical importance in teaching students of engineering and medical universities the physical basics of modern methods and technologies. Keywords: nuclear magnetic resonance, physics course, difficulty levels, engineering university, medical university, production technologies, medical technologies

SSwsrNet: A Semi-Supervised Few-Shot Learning Framework for Wireless Signal Recognition

SSwsrNet: A Semi-Supervised Few-Shot Learning Framework for Wireless Signal Recognition

Multiple Access in Large-Scale LoRaWAN: Challenges, Solutions, and Future Perspectives

Enabling energy-efficient and long-distance wireless networking is expected by various Internet-of-Things systems and consumer electronics applications. Low Power Wide Area Networks can commendably satisfy this requirement because of their combination of low-power and long-range features. Thereinto, open-standard Long Range Wide Area Network (LoRaWAN) is the representative player with hundreds of deployment cases worldwide. Unfortunately, current multiple access (MA) strategy for LoRaWAN has been proved to incur severe wireless signal interference under large-scale deployment. This is the inherent hindrance for current LoRaWAN to support large-scale wireless networking. In this context, this article aims to provide a detailed tutorial of MA issues in large-scale LoRaWAN for the first time. We start with several practical use cases of large-scale LoRaWAN. We then explain the detailed challenges of large-scale LoRaWAN networking. Representative MA solutions for better LoRaWAN networking are then described and compared. Future research directions for enhanced MA protocol design are also discussed.

Microconfined Assembly of High-Resolution and Mechanically Robust EGaIn Liquid Metal Stretchable Electrodes for Wearable Electronic Systems.

Stretchable electrodes based on liquid metals (LM) are widely used in human-machine interfacing, wearable bioelectronics, and other emerging technologies. However, realizing the high-precision patterning and mechanical stability remains challenging due to the poor wettability of LM. Herein, a method is reported to fabricate LM-based multilayer solid-liquid electrodes (m-SLE) utilizing electrohydrodynamic (EHD) printed confinement template. In these electrodes, LM self-assembled onto these high-resolution templates, assisted by selective wetting on the electrodeposited Cu layer. This study shows that a m-SLE composed of PDMS/Ag/Cu/EGaIn exhibits line width of ≈20µm, stretchability of ≈100%, mechanical stability ≈10000 times (stretch/relaxation cycles), and recyclability. The multi-layer structure of m-SLE enables the adjustability of strain sensing, in which the strain-sensitive Ag part can be used for non-distributed detection in human health monitoring and the strain-insensitive EGaIn part can be used as interconnects. In addition, this study demonstrates that near field communication (NFC) devices and multilayer displays integrated by m-SLEs exhibit stable wireless signal transmission capability and stretchability, suggesting its applicability in creating highly-integrated, large-scale commercial, and recyclable wearable electronics.

Extended segmentectomy for intersegmental lesions with intraoperative surgical margin assessment by radiofrequency identification markers

ObjectiveWe developed a technique to determine deep surgical margins using radiofrequency identification markers. This study assessed the feasibility of this technique during extended segmentectomy of intersegmental lesions. MethodsA single-center, prospective, single-arm study was performed from 2020 to 2023. Small pulmonary lesions suspicious for malignancy locating the virtual intersegmental plane based on 3-dimensional imagery were included. Markers were placed in the vicinity of the lesions using electromagnetic navigation bronchoscopy. In addition to indocyanine green injection, surgeons used wireless signal strength to determine the best resection line without lung palpation to obtain surgical margins of 10 mm or the same size as the tumor. ResultsWe analyzed 75 lesions in 75 patients. Median lesion size and depth from the pleura were 12.0 mm and 23.6 mm, respectively. Three-dimensional imagery identified lesions at a median distance of 7.0 mm from the virtual intersegmental plane. The median marker-lesion and marker-virtual intersegmental plane distances were 5.8 mm and 4.9 mm, respectively. Complex segmentectomy was performed in 64 of 75 patients (85.3%). The indocyanine green and preoperative simulated intersegmental lines agreed in 92.0% (69/75). In 6 cases (8.0%), the resection line was determined using radiofrequency identification markers to obtain adequate margins because the indocyanine green undyed area was smaller than the preoperatively simulated one. In 1 patient, planned segmentectomy was converted to lobectomy because of a misplaced radiofrequency identification marker (1.3%). The successful tumor resection rate was 98.7%. The median surgical margin was 16.0 mm. ConclusionsUse of radiofrequency identification markers enabled precise extended segmentectomy with adequate surgical margins.

A Wireless Signal Correlation Learning Framework for Accurate and Robust Multi-Modal Sensing

A Wireless Signal Correlation Learning Framework for Accurate and Robust Multi-Modal Sensing

Performance Evaluation of Carrier-Frequency Offset as a Radiometric Fingerprint in Time-Varying Channels.

The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios. It is still unclear, however, how the CFO detection capability would hold up in more dynamic time-varying channels where there is a higher mobility. This paper experimentally demonstrates the identification accuracy of CFO for wireless devices in time-varying channels. To this end, a software-defined radio (SDR) testbed is deployed to collect CFO values in real environments, where real transmission and reception are conducted in a vehicular setup. The collected CFO values are used to train machine-learning (ML) classifiers to be used for device identification. While CFO exhibits good detection performance (97% accuracy) for low-mobility scenarios, it is found that higher mobility (35 miles/h) degrades (72% accuracy) the effectiveness of CFO in distinguishing between legitimate and non-legitimate transmitters. This is due to the impact of the time-varying channel on the quality of the exchanged pilot signals used for CFO detection at the receivers.