Search Results (78)

Long Range (LoRa) is one of the promising Low-Power Wide-Area Network technologies to achieve a strong anti-noise ability due to the modulation of the chirp spread spectrum in low-power and long-distance communications. However, LoRa suffers the problem of packet collisions. Hence, we propose QR−LoRa, a novel PHY-layer scheme that can transmit data in both amplitude and frequency dimensions simultaneously. For the amplitude modulation, we modulate the constant envelope of a LoRa chirp with a cyclic right-shifted ramp signal, where the cyclic right-shifted position carries the data of the amplitude modulation. We adopt the standard LoRa for frequency modulation. We prototype QR−LoRa on the software-defined radio platform USRP N210 and evaluate its performance via simulations and field experiments. The results show the bit rate gain of QR−LoRa is up to 2× compared with the standard LoRa device. Full article

Based on rolling contact fatigue life experiments, this study systematically investigates the effect of ultrasonic surface rolling processing (USRP) with a composite diamond-like carbon (DLC) coating on the rolling contact fatigue life of bearings through characterization and analysis. The results show that the USRP-composite DLC coating forms a synergistic mechanism between the coating and the substrate on the surface of specimens: the DLC coating resists surface wear with its high hardness and low friction coefficient, while USRP reduces substrate deformation and crack growth by decreasing surface roughness, increasing substrate hardness, and introducing residual compressive stress. Additionally, USRP enhances the adhesion between the coating and the substrate. The average wear volume of the USRP-composite DLC-coated specimens is 3.73 × 10¹¹ μm³, which is 30.95% lower than that of USRP-treated specimens and 85.38% lower than that of untreated specimens. The average fatigue life of the USRP-composite DLC-coated specimens is 6.55 × 10⁶ cycles, which is 94.94% higher than that of USRP-treated specimens and 208.24% higher than that of untreated specimens. Full article

316LN stainless steel (316LN SS) with a gradient structure was produced by ultrasonic surface rolling processing (USRP). The surface quality of the 316LN SS specimen was improved significantly after the USRP. The experimental results showed that with an increasing number of rolling passes, the thickness of the gradient structure layer increased, and the microhardness decreased in a gradient from the surface to the matrix. The results also indicated that the optimal parameters were as follows: 220 rad/min lathe speed, 0.11 mm rolling space, 0.2 rad/min feed rate, and 5 rolling passes. Under these parameters, the tested surface residual compressive stress (SRCS) value was nearly 32 times higher than that achieved after conventional processing on the surface of 316LN stainless steel. Moreover, the microstructure exhibits an increase in the subgrain boundary density and low-angle grain boundaries (LAGBs, misorientation < 15°) of the steel, providing an easy way to enhance the properties, including the mechanical and corrosion resistance of 316LN stainless steel. Full article

Researchers are actively pursuing advancements in convolutional neural networks and their application in anti-drone systems for drone classification tasks. Our study investigates the hypothesis that the accuracy of drone classification in the radio frequency domain can be enhanced through a hybrid approach. Specifically, we aim to combine fuzzy logic for edge detection in images (the spectrograms of drone radio signals) with convolutional and convolutional recurrent neural networks for classification tasks. The proposed FLEDNet approach introduces a tailored engineering strategy designed to tackle classification challenges in the radio frequency domain, particularly concerning drone detection, the identification of drone types, and multiple drone detection, even within varying signal-to-noise ratios. The strength of this tailored approach lies in implementing a straightforward edge detection method based on fuzzy logic and simple convolutional and convolutional recurrent neural networks. The effectiveness of this approach is validated using the publicly available VTI_DroneSET dataset across two different frequency bands and confirmed through practical inference on the embedded computer NVIDIA Jetson Orin NX with radio frequency receiver USRP-2954. Compared to other approaches, FLEDNet demonstrated a 4.87% increase in accuracy for drone detection, a 13.41% enhancement in drone-type identification, and a 7.26% rise in detecting multiple drones. This enhancement was achieved by integrating straightforward fuzzy logic-based edge detection methods and neural networks, which led to improved accuracy and a reduction in false alarms of the proposed approach, with potential applications in real-world anti-drone systems. The FLEDNet approach contrasts with other research efforts that have employed more complex image processing methodologies alongside sophisticated classification models. Full article

As advanced structural materials, titanium alloys have found extensive applications in aerospace, medical devices, and precision electronics industries, serving as critical components for achieving lightweight designs in high-end equipment. In aerospace applications, titanium alloy components are frequently subjected to complex thermo-mechanical loading conditions involving varying temperature levels and multiaxial stress states, which may induce progressive fatigue damage accumulation and ultimately lead to premature fracture failures. This study conducts a systematic investigation into the fatigue damage mechanisms of aerospace-grade titanium alloys under service conditions, with particular emphasis on elucidating the synergistic effects of microstructural characteristics, surface integrity parameters, and operational temperature variations on fatigue behavior. Through comprehensive analysis, the research reveals that surface modification techniques, including shot peening (SP), ultrasonic surface polling process (USRP), and laser shock peening (LSP), significantly enhance fatigue performance through two primary mechanisms: (1) the generated residual compressive stress fields effectively inhibit crack initiation and retard propagation rates; (2) improved surface integrity characteristics, such as reduced roughness and work-hardened layers, contribute to enhanced oxidation resistance thereby preserving structural integrity. Full article

The surface roughness, surface hardness, tensile properties and friction-wear properties were characterized, in comparison with those of the traditional turned cutting, electropulsing treatment (EP) and ultrasonic surface-rolling process (USRP) sample. The surface microstructure was obviously refined after USRP and EP-USRP, with a fine-grain depth of 60 μm and 100 μm, respectively. The surface roughness significantly decreases at first, and then gradually increases after surface-strengthening modification. The lowest roughness of 0.035 μm and 0.040 μm is obtained for the USRP and EP-USRP samples, respectively, which is about 12 times less than that of the turning surface roughness of 0.421 μm. The surface hardness increases from 280 HV to 360 HV after strengthening modification. The super tensile property of 30CrNi2Mo steel is obtained for the USRP, for which the yield strength, tensile strength, elongation and yield-to-strength ratio are 743 MPa, 961 MPa, 11% and 0.773, respectively. The friction coefficients in the turning state, USRP and EP-USRP are 0.37, 0.35 and 0.4, respectively. Ultrasonic composite-strengthening modification can increases the surface hardness, and obtains gradient microstructure on the material surface, which endows the material with better surface properties. Full article

The frequency diverse array (FDA) is an architecture capable of beamforming in both range and angle, improving upon the traditional phased array (PA) which can only achieve beamforming in angle. The FDA employing directional modulation (DM) for secure directional communications (SDC) can reduce bit error rates (BERs) in both range and angle, again improving upon the traditional PA which can only reduce BER in angle. In this paper, we document the challenges involved in the design and implementation of a two-element linear FDA employing fast-time binary phase-shift keying (BPSK) modulations. We also show that the experimentally collected field data match well with the results of simulations based on our analytical model. Full article

In this paper, a differential chaotic shift keying communication system based on noise reduction with orthogonal double bit rate (NR-ODBR-DCSK) is proposed. The system incorporates Walsh orthogonalization at the transmitter side to orthogonalize the information signals so that two mutually orthogonal signals can be superimposed. At the receiving end, because the principle of orthogonal signals is used, it achieves the characteristic of double information transmission rate for information signal transmission while avoiding the problem of chaotic synchronization. In addition, the system employs a noise reduction transmission mechanism, which reduces the noise variance in the received signal, further reducing the BER of the system and thus improving the performance of the communication system. By analyzing the signal format of the system, the transmitter and receiver structures of the communication system are designed. Subsequently, theoretical analyses and simulations in an additive white Gaussian noise (AWGN) channel demonstrate the good performance of the system, including a low bit error rate (BER) and a good data-energy to bit-energy ratio (DBR). Finally, a simulation test of the NR-ODBR-DCSK system for a semi-physical communication system was carried out using two USRP devices to verify the experimental feasibility of the system. The simulation analysis results show that comparative analyses with conventional DCSK and SR-DCSK systems highlight the superior performance of the NR-ODBR-DCSK system. Full article

This paper presents the development and validation of a hybrid beamforming system based on software-defined radio (SDR), designed for telecommunications engineering education. The system provides an agile and user-friendly platform that allows students to observe, test, and evaluate beamforming techniques in real time. The platform integrates a multichannel SDR device (USRP N310) with traditional radiofrequency equipment and open-source software, facilitating hands-on learning experiences. The paper details the proposed hardware and software architecture and documents the calibration and validation phases. The testing and validation processes were conducted using a 3.5 GHz antenna array in both indoor and outdoor environments. The results demonstrated the system’s effectiveness in achieving the desired beam orientations, with experimental results aligning closely with simulation and theoretical predictions. Significant differences in the radiation patterns observed between the indoor and outdoor measurements were documented, highlighting the impact of environmental factors on beamforming performance. The insights gained from this research provide valuable contributions to the education of future telecommunications engineers, enhancing their understanding of practical beamforming applications and the integration of modern SDR technology. Full article

Landslides are widespread and global geological disasters, affecting millions of people and causing numerous deaths each year. Despite technological advances, it is still difficult to accurately prevent landslides. Due to its geography and climatic conditions, Ecuador has been significantly affected by landslides, and the city of Penipe remains one of the most affected. For this reason, a low-cost SDRadar system was designed to detect translational landslide risk levels by measuring the electrical permittivity of Andepts subtype soils. Controlled laboratory tests were performed with soil samples to relate permittivity values to landslide risk levels, and subsequently field tests were carried out in Penipe to determine the efficiency of the methodology. The results showed that moderate humidity is important for soil compaction, regardless of the degree of sloping. However, with permittivity values lower than 1.5 or higher than 20, the risk of landslides is very high on slopes greater than 45°. These results were compared with records of the serious landslides that occurred in June 2024 in Ecuador, in which rainfall intensity values similar to those obtained in this study were recorded, suggesting that this system can prevent future disasters. Full article

With the widespread use of unmanned aerial vehicles (UAVs), the detection and identification of UAVs is a vital security issue for the safety of airspace and ground facilities in the no-fly zone. Telemetry radios are important wireless communication devices for UAVs, especially in UAVs beyond the visual line of sight (BVLOS) operating mode. This work focuses on the UAV identification approach using transient signals from UAV telemetry radios instead of the signals from UAV controllers that the former research work depended on. In our novel UAV Radio Frequency (RF) identification system framework based on telemetry radio signals, the $EC-\alpha$ algorithm is optimized to detect the starting point of the UAV transient signal and the detection accuracy at different signal-to-noise ratios (SNR) is evaluated. In the training stage, the Convolutional Neural Network (CNN) model is trained to extract features from raw I/Q data of the transient signals with different waveforms. Its architecture and hyperparameters are analyzed and optimized. In the identification stage, the extracted transient signals are clustered through the Self-Organizing Map (SOM) algorithm and the Clustering Signals Joint Identification (CSJI) algorithm is proposed to improve the accuracy of RF fingerprint identification. To evaluate the performance of our proposed approach, we design a testbed, including two UAVs as the flight platform, a Universal Software Radio Peripheral (USRP) as the receiver, and 20 telemetry radios with the same model as targets for identification. Indoor test results show that the optimized identification approach achieves an average accuracy of 92.3% at 30 dB. In comparison, the identification accuracy of SVM and KNN is 69.7% and 74.5%, respectively, at the same SNR condition. Extensive experiments are conducted outdoors to demonstrate the feasibility of this approach. Full article

Data acquisition systems that receive analog signals, convert them to digital, and perform signal processing are used in a variety of systems that use acoustics, radar, sonar, indoor localization, and navigation. The previous systems, such as NI USRP-RIO, are expensive to build, and the number of signals a single device can receive is limited to between two and four. In order to receive more channels of signals, multi-channel data acquisition systems using ADCs operating at tens of MSPS have been proposed. However, these systems require additional processing time because data acquisition and signal processing are performed on different devices. In this paper, we propose a multi-channel data acquisition system using a 16-channel ADC that can support up to 100 MSPS. In particular, to reduce unnecessary signal transmission time, we propose a one-chip structure where all processes are performed on a single chip. Also, we propose a data acquisition system that applies pipelining techniques to enable real-time processing. To verify the proposed system, we used TI ADS52J90 and a Kintex UltraScale KCU105 evaluation board, and confirmed that it is possible to receive and process all channels simultaneously. Furthermore, it is possible to configure a real-time system by adjusting the speed of the signal-processing operation and the speed of the communication interface. Therefore, the proposed system is expected to reduce the cost of system construction by performing signal reception and processing with a single chip, and to reduce the time required for overall signal processing. Full article

Ultrasonic surface rolling process (USRP) has the potential to improve the surface mechanical properties of metal components with platelike or cylindrical macrostructure, but its effect on spherical surfaces remains to be studied in depth. In order to investigate the effect of USRP on the surface roughness, hardness and wear resistance of a spherical joint bearing made of GCr15 bearing steel, ultrasonic rolling strengthening was carried out on a spherical bearing surface under various conditions. The surface roughness and hardness variations of samples before and after strengthening were investigated. It was found that the USRP strengthening process can effectively enhance the surface properties of GCr15 spherical bearing materials, reduce the surface roughness by more than 45%, and increase the surface hardness by more than 10%. Friction and wear tests were carried out before and after ultrasonic rolling. The results show that the friction coefficient of the bearing surface can be reduced by 28%, and that the wear volume can be reduced by 29%. The variation in the friction coefficient correlated to the variance of wear volume as the reinforcement changes. Full article

The demand for titanium alloy has been increasing in various industries, including aerospace, marine, and biomedical fields, as they fulfilled the need for lightweight, high-strength, and corrosion-resistant material for modern manufacturing. However, titanium alloy has relatively low hardness, poor wear performance, and fatigue properties, which limits its popularization and application. These disadvantages could be efficiently overcome by surface strengthening technology, such as the ultrasonic surface rolling process (USRP). In this study, the true thermo-mechanical deformation behavior of Ti-6Al-4V was obtained by dynamic mechanical experiment using a Hopkinson pressure bar. Moreover, USRP was applied on the Ti-6Al-4V workpiece with different parameters of static forces to investigate the evolution in surface morphology, surface roughness, microstructure, hardness, residual stress, and fatigue performance. The strain rate and temperature during the USRP of Ti-6Al-4V under the corresponding conditions were about 3000 s⁻¹ and 200 °C, respectively, which were derived from the numerical simulation. The correlation between the true thermo-mechanical behavior of Ti-6Al-4V alloy and the USRP parameters of the Ti-6Al-4V workpiece was established, which could provide a theoretical contribution to the optimization of the USRP parameters. After USRP, the cross-sectional hardness distribution of the workpiece was shown to initially rise, followed by a subsequent decrease, ultimately to matrix hardness. The cross-sectional residual compressive stress distribution of the workpiece showed a tendency to initially reduce, then increase, and finally decrease to zero. The fatigue performance of the workpiece was greatly enhanced after USRP due to the effect of grain refinement, work hardening, and beneficial residual compressive stress, thereby inhibiting the propagation of the fatigue crack. However, it could be noted that the excessive static force parameter of USRP could induce the decline in surface finish and compressive residual stress of the workpiece, which eliminated the beneficial effect of the USRP treatment. This indicated that the choice of the optimal USRP parameters was highly crucial. This work would be conducive to achieving high-efficiency and low-damage USRP machining, which could be used to effectively guide the development of high-end equipment manufacturing. Full article

In this paper, we explore several widely available software-defined radio (SDR) platforms that could be used for locating with the signal Doppler frequency (SDF) method. In the SDF, location error is closely related to the accuracy of determining the Doppler frequency shift. Therefore, ensuring high frequency stability of the SDR, which is utilized in the location sensor, plays a crucial role. So, we define three device classes based on the measured frequency stability of selected SDRs without and with an external rubidium clock. We estimate the localization accuracy for these classes for two scenarios, i.e., short- and long-range. Using an external frequency standard reduces the location error from 20 km to 30 m or 15 km to 2 m for long- and short-range scenarios, respectively. The obtained simulation results allowed us to choose an SDR with appropriate stability. The studies showed that using an external frequency standard is necessary for minimizing SDR frequency instability in the Doppler effect-based location sensor. Additionally, we review small-size frequency oscillators. For further research, we propose two location sensor systems with small size and weight, low power consumption, and appropriate frequency stability. In our opinion, the SDF location sensor should be based on the bladeRF 2.0 micro xA4 or USRP B200mini-i SDR platform, both with the chip-scale atomic clock CSAC SA.45s, which will allow for minor positioning errors in the radio emitters. Full article