Search Results (151)

This paper investigates the feasibility of 3D self-localization and tracking using chipless radio frequency identification (RFID) tags operating in the terahertz (THz) frequency band. The primary objective is to achieve sub-millimeter (sub-mm) localization and tracking accuracy while minimizing reliance on external infrastructure. To this end, a hybrid localization framework is proposed that jointly exploits round-trip time-of-flight (RToF) and angle-of-arrival (AoA) measurements to enhance localization performance. Although near-field propagation effects are inherently significant in the considered THz operating regime, a simplified far-field approximation is adopted to facilitate tractable system modeling and analytical development. The proposed framework is further extended to dynamic scenarios through an extended Kalman filter (EKF)-based tracking algorithm, which incorporates temporal state evolution to improve estimation robustness under noisy measurements. Furthermore, the Cramér–Rao lower bound (CRLB) for the hybrid RToF-AoA system is derived to establish the fundamental limits of localization accuracy under varying system configurations and measurement conditions. Simulation results demonstrate that the proposed approach is capable of achieving sub-mm localization and tracking accuracy with a highly constrained anchor infrastructure, including operation with a single anchor in the considered scenario. These findings highlight the potential of THz chipless RFID technology as a promising enabling solution for next-generation high-accuracy localization and tracking applications. Full article

Multirotor unmanned aerial vehicles (UAVs) rely on electronic speed controllers (ESCs) that decode motor commands from pulse-width modulation (PWM) signals, making the flight-controller-to-ESC command path a physical-layer attack surface for intentional electromagnetic interference (IEMI). This paper presents a mechanism-based analysis of IEMI attacks that induce motor stoppage in UAV brushless DC motor controllers. We develop a timing-error model in which a sinusoidal disturbance on the PWM line shifts the detected edge instants and drives the decoded pulse width into stop-equivalent regimes, and we show that the disturbance reaching the ESC’s thresholding node is shaped by a frequency-selective cascade of the PWM cable’s coupling response and the ESC’s input-path transfer function. We experimentally characterize this model on five commercial ESCs through conducted and radiated injection. The measured thresholds differ by more than an order of magnitude across ESCs and are reordered between frequency bands and injection modes; comparing conducted and radiated results allows us to attribute these differences primarily to the cable coupling response and reveals cases where it either hides or amplifies an ESC’s susceptibility. The susceptible frequency also shifts with PWM cable length in qualitative agreement with transmission-line resonance, confirming that observed radiated susceptibility reflects the joint design of ESC and cable rather than a single intrinsic property. The cable lengths examined here (45–125 cm) are longer than those of compact multirotors and were chosen to place resonances within our antenna’s band; we discuss the implications of this choice and identify shorter, deployment-realistic cables as a priority for future work. Full article

Alternate wetting and drying (AWD) irrigation reduces CH₄ emissions from flooded rice but amplifies N₂O pulses; identifying candidate phenological windows for the remote screening of greenhouse gas (GHG) fluxes remains challenging with small datasets. In a single-site, single-season exploratory study at INIA Vista Florida (Lambayeque, Peru), eight UAV flights were paired with eight PlanetScope SuperDove scenes ($|\Delta |\le 1$ d) and closed-chamber CH₄, N₂O and CO₂ fluxes under four water regimes (CF, AWD₅, AWD₁₀, AWD₂₀; 96 sub-plot × date observations). Multivariate explanatory power was assessed by bootstrap Ridge regression on each sensor’s native predictors (VI + GLCM + $T_{\mathrm{mean}}$ for the UAV, VI for PlanetScope). Maximum tillering (79 DAS) emerged as a candidate UAV window, ranking in the top three for all gases through GLCM textures, whereas PlanetScope peaked at Mid-boot and Late-boot (103–107 DAS), with median ${\widetilde{R^2}}_{\mathrm{UAV}}$ at $0.34$–$0.71$ and ${\widetilde{R^2}}_{\mathrm{Planet}}$ at $0.20$–$0.60$. Nested Leave-One-Plot-Out (LOPO) validation gave $R_{\mathrm{CV}}^2$ between $+0.57$ and $+0.69$ for four of six platform × gas combinations (UAV-CH₄ and Planet-N₂O stayed weak), and $T_{\mathrm{mean}}$ was decisive for N₂O on the UAV ($\Delta R^2=+0.48$). Repeating the stage selection inside every LOPO fold preserved the leading combinations and their ranking. These exploratory windows and sensor-native descriptors need multi-site, multi-season validation before operational use. Full article

A probability-based model (PBM) is developed to predict the evolution of a population of impinging droplets on a solid substrate and the eventual transition between dropwise and filmwise regimes. A dedicated heat transfer model is designed, in order to estimate the evaporating mass flux when the solid substrate is heated. Statistical information such as the droplet size distribution and the influence of surface wettability, required by the PBM, are derived using a previously developed high-fidelity individual-based model (IBM). The PBM is verified with the high-fidelity model for a small patch of solid substrate. Then, validation with experimental evidence from the literature is carried out in the case of in-flight ice on the NACA0012 airfoil. Results show that the present PBM is capable of investigating in-flight ice problems and can be integrated with a CFD analysis of the air flow past an airfoil flying through a cloud of supercooled droplets to predict the possible onset of ice accretion on the airfoil surface. Compared to Messinger-like models, the influence of surface morphology on runback water flow is incorporated in the PBM through the modeling of a discontinuous wetting layer, contributing to the design of passive and active anti-icing systems. Full article

Global Navigation Satellite Systems (GNSS)-denied environments pose significant challenges for autonomous drone navigation, requiring robust visual localization systems capable of real-time performance. Existing approaches either sacrifice accuracy for speed or fail to adapt to varying flight altitudes and orientations, limiting their practical deployment. We present Real-Time Elevation and Orientation-Aware Localization Architecture (REOLA), a visual localization system that combines similarity-driven autonomous window sizing, element-wise correlation-based orientation detection, and reinforcement learning with human feedback (RLHF) enhancement for publicly available satellite imagery. On desktop hardware (i7-10700K + RTX 3070), the REOLA achieved approximately 59 FPS performance with sub-5-m accuracy across diverse flight conditions through intelligent similarity-based matching, combined with efficient MobileNet-V3 embeddings and FAISS similarity search. For embedded deployment on NVIDIA Jetson Orin Nano, the system achieved 22.5 FPS, meeting real-time requirements for autonomous drone localization. The system autonomously selects optimal window sizes corresponding to the current elevation and determines drone orientation through element-wise correlation scoring across discrete rotation angles. Enhanced through RLHF, the REOLA achieved a $97.1\%$ success rate (sub-5-m localization) while processing frames in 17 milliseconds on desktop hardware (44.4 ms on embedded hardware), providing a substantial margin over real-time requirements. The approach demonstrates particular superiority over traditional keypoint-based methods in challenging environments with repetitive patterns such as agricultural fields, rocky mountains, dense forests, and grasslands, where conventional keypoint detection struggles. We explicitly identify featureless sand dune deserts and open-sea or coastal water flights as out of scope, since the reference satellite imagery in those regimes does not contain stable landmarks. Full article

Unmanned aerial vehicle (UAV)-assisted millimeter-wave (mmWave) and terahertz (THz) communications are promising enablers of ultra-reliable and low-latency communication in next-generation wireless networks. However, the initial access and beam alignment process remains challenging because highly directional beams must be rapidly aligned in a three-dimensional environment. In this paper, we investigate a risk-aware beam alignment framework for UAV-assisted mmWave/THz systems, where user equipment scans a 3D spherical region to detect UAV base stations. The objective is to jointly minimize the expected cell-search latency and its variance while satisfying detection-failure and link-quality constraints. To solve this non-convex optimization problem efficiently, we employ the Lévy Self-Renewable Flow Direction Algorithm (LSRFDA), which combines Lévy-flight exploration with self-renewal to improve convergence robustness. A unified propagation model is adopted to cover both mmWave and THz regimes by incorporating free-space spreading loss and frequency-dependent molecular absorption. Extensive Monte Carlo simulations compare the proposed approach with Particle Swarm Optimization, Random Search, Reinforcement Learning, and PPO-Lagrangian methods. The results show that LSRFDA achieves lower latency, lower latency variation, more reliable detection, and lower energy consumption across a wide range of UAV densities and coverage radii. These outcomes highlight the effectiveness of risk-aware geometric optimization for fast and dependable initial access in UAV-assisted 5G mmWave and 6G THz networks. Full article

Flapping-wing flight offers a promising solution for aerial mobility in low-density environments such as the Martian atmosphere, where conventional rotorcraft faces significant performance constraints. However, the coupled aerodynamic and structural mechanisms governing lift generation at low Reynolds numbers remain insufficiently understood. This study investigates the aeroelastic and unsteady aerodynamic behaviour of a bio-inspired flapping wing using an integrated experimental–numerical framework. High-speed imaging is employed to extract representative wing kinematics, including flapping frequency, stroke amplitude, and rotational motion. A geometrically scaled wing model is developed based on Reynolds number similitude and analysed using finite element methods to characterise its dynamic response. Aeroelastic behaviour is evaluated through modal transient simulations, while aerodynamic performance is assessed using both vortex-lattice modelling and computational fluid dynamics. The results show strong coupling between bending and torsional modes, with the structural response highly dependent on excitation frequency relative to the natural modes. Near-resonant conditions lead to amplified deformation and distinct phase relationships, while aerodynamic simulations reveal vortex-dominated lift generation. These findings provide a physics-based framework for the design and analysis of flapping-wing systems operating in low-Reynolds-number and low-density flight regimes. Full article

Lift-plus-cruise electric vertical takeoff and landing (eVTOL) aircraft exhibit complex stability characteristics during transition flight, when rotor-borne and wing-borne regimes coexist. This work investigates the dynamic stability of a lift-plus-cruise eVTOL using a nonlinear six-degree-of-freedom model incorporating aerodynamic forces, tractor propulsion, and vertical lifter dynamics. Linearization about representative trimmed conditions enables longitudinal and lateral–directional modal analysis. The results identify a critical near-stall region where lift-curve slope reduction markedly decreases short-period damping. Residual lifter authority partially compensates for this degradation, improving stability in the transition regime. To ensure smooth control transfer, an airspeed-dependent blending strategy between hover and fixed-wing controllers is implemented. Comparative analyses show that a sigmoid blending law improves the minimum short-period damping ratio relative to a linear strategy while preserving similar overall damping variation. Closed-loop simulations of a complete mission profile demonstrate the effectiveness of the proposed approach and reveal an asymmetric dynamic response between hover-to-forward and forward-to-hover transitions. These findings provide a physically grounded explanation for stability degradation during transition and establish practical guidelines for control authority blending in lift-plus-cruise eVTOL aircraft. Full article

A new class of modified minimum state error variance (MSEV) state-space based optimal linear quadratic Gaussian (LQG) regulators for closed-loop structures with estimated feedback has been proposed in this article. The negative feedback path is designed as the cascade of the digital LQG regulator and discrete Kalman state observer. The proposed design enables tracking of a time-varying reference input using the predictive control approach. Moreover, the proposed tracking method utilizes a multivariable continuous-time Cauchy state-space model of nonlinear, nonstationary dynamic systems. The resulting control strategy is approximately optimal, as the optimality of the LQG design holds locally for each linearized model around the respective operating point and does not extend to the global nonlinear system. In this sense, starting from the prespecified nominal state trajectory to be tracked, a numerical optimization procedure minimizing the squared tracking error at each step by using the Nelder–Mead direct search simplex algorithm under the required constraints on the input signal has been developed. The LQG regulator and Kalman state observer are designed by utilizing the linear discrete-time state variable models that properly approximate the nonlinear system dynamics across the nominal state trajectory. The performance of the proposed design is validated by simulating a six-degree-of-freedom nonlinear aircraft model across typical flight regimes. Full article

Surface orientation can influence the aerodynamic response of modern soccer balls, particularly in the drag crisis regime. This study quantified the orientation-dependent aerodynamic characteristics of the FIFA World Cup match ball Trionda using a single specimen and examined how these differences affect simulated flight at sea level and 1500 m altitude. Two reproducible reference orientations were defined: a red-panel-centered orientation (Series A) and a seam-junction-centered orientation (Series B). Each reference orientation was rotated by 0°, 90°, and 180°, resulting in six fixed-orientation conditions. Wind tunnel measurements were repeated three times per condition to obtain drag, lift, and side-force coefficients, and two-dimensional non-spinning flight simulations were performed for representative long-kick and free-kick conditions. All six orientations exhibited drag crisis behavior, but the transition response magnitude, subcritical drag level, and supercritical drag state differed among conditions. The representative transition region occurred at approximately Re = 2.0 × 10⁵ to 2.5 × 10⁵. Among the tested conditions, B-90 showed the lowest full-range mean drag coefficient (0.231), whereas A-90 showed the highest (0.266). In the simulations, lower drag orientations consistently produced longer flight ranges, and the B-90 > A-90 ordering was preserved across representative launch conditions and the expanded parametric comparison. These findings indicate that the aerodynamic response of Trionda cannot be represented adequately by a single mean drag coefficient and that surface orientation should be considered in aerodynamic characterization and flight prediction. Full article

The transient mechanism of dual-boundary dynamic opening in the inlet during stage transition of an integral solid rocket ramjet (ISRR) remains insufficiently understood. To address this issue, a combined approach involving numerical simulations and free-jet experiments was employed. A parametric model describing the time-sequenced opening of inlet and outlet cover was established. The influences of sequence and progression of opening and flight conditions on transient flow evolution and inlet stability were systematically examined. It is found that when the inlet is opened first, a “dead cavity” tends to form inside the inlet, which subsequently triggers pronounced pressure oscillations. Under baseline conditions, the peak outlet pressure reaches approximately 0.90 MPa, with a dominant frequency of about 66.7 Hz. Conversely, when the outlet is opened first, the cavity-induced oscillation is effectively suppressed; however, a transient “flow choking” overpressure and a delayed establishment of the flow field are observed. The discrepancies between simulations and experiments for key pressure characteristics under two representative opening modes are maintained within 5%, confirming the robustness of the proposed methodology. Further analysis reveals that increasing the Mach number markedly intensifies flow instability and reduces the stability margin, whereas higher flight altitudes help attenuate cavity oscillations. A strong coupling between the opening rate and temporal sequence is also identified. Specifically, for inlet-first scenarios, a slower inlet opening combined with a rapid outlet opening is preferable, while for outlet-first cases, rapid opening on both sides yields better performance. On this basis, a “stability window map” defined by the temporal difference (Δt) and opening duration (Topen) is proposed. This map delineates the distributions of stable, transitional, and hazardous regimes under varying conditions, which may offer a quantitative reference for adaptive control strategies in the ISRR stage of transition. Interestingly, these findings suggest that slight timing adjustments could substantially reshape the transient flow behavior. Notably, the introduction of the dual-boundary temporally coordinated forcing leads to flow responses within the inlet that exhibits pronounced path dependence and non-uniqueness. Such behavior deviates from the conventional understanding established under the single-boundary frameworks, where transient mode-transition processes were typically assumed to be uniquely determined. More importantly, these findings offer a renewed physical interpretation of inlet mode-transition dynamics, thereby providing both quantitative support and practical guidance for the adaptive design of ISRR transition control strategies. In particular, the results suggest that incorporating multi-boundary temporal effects could significantly enhance the robustness and flexibility of the control-law formulation. Full article

Reliable altitude and vertical speed estimation are fundamental for unmanned aerial vehicle (UAV) autonomous flight, especially during low-altitude operations such as takeoff and landing. Barometric altimeters are widely used due to their low cost, high availability, and good long-term stability, providing smooth altitude trends over a wide operating range. However, barometric measurements are indirectly inferred from static pressure and are therefore sensitive to local airflow disturbances. In particular, rotor downwash and ground effect-induced pressure perturbations near the surface can introduce significant biases and short-term fluctuations in barometric altitude, which propagate into erroneous vertical speed estimates during critical flight phases. Time-of-flight (TOF) altimeters, such as radar or laser sensors, provide direct above-ground-level (AGL) measurements and are largely insensitive to ground effect-related pressure disturbances. Within their limited operational range, TOF altimeters typically offer higher accuracy and lower short-term noise compared with barometric altitude. Nevertheless, TOF sensors are characterized by a restricted valid measurement range and frequently exhibit non-ideal behaviors in real-world UAV operations, including out-of-range outputs, frozen measurements, and in-range biased readings. These anomalies violate the nominal sensor assumptions used in conventional Kalman filter-based fusion and can significantly degrade estimation performance if not properly handled. This paper proposes a hybrid Kalman–rule-based altitude estimation framework that fuses barometric and TOF altitude measurements to exploit their complementary characteristics while mitigating their respective limitations. A vertical dynamic state-space model is formulated to jointly estimate altitude, vertical velocity, accelerometer bias, and ground height offset. A rule-based anomaly detection and classification module is developed to identify multiple TOF altimeter failure modes observed in operational UAV flights. The detected anomaly states are incorporated into the Kalman filter to adaptively weight, accept, or reject TOF measurements, thereby improving robustness against sensor non-idealities. The proposed approach is validated using 39 real UAV flight logs covering diverse flight regimes, including low-altitude maneuvers, cruise, and autonomous landing. Experimental results show that the proposed framework provides more stable and robust altitude and vertical speed estimation under practical sensor anomaly conditions compared with conventional barometer-only and standard Kalman fusion configurations. These results demonstrate the practical effectiveness of the proposed method for fault-aware altitude estimation in UAV autonomous flight. Full article

This paper proposes a computationally efficient algorithm for nonlinear optimal guidance with a predefined final flight path angle. Although numerous impact angle guidance methods based on optimal control theory exist, a lack of efficient calculation procedures remains for the exact nonlinear engagement model, leaving practical hardware implementation challenges for the end-user. A fixed-structure algorithm with deterministic computational burden is developed for real-time onboard integration. The performance and optimality of the algorithm are verified through a comparative study with established guidance laws. Unlike methods relying on line-of-sight rate or time-to-go estimations, the proposed approach uses a closed-feedback form based on standard navigation data. A closed-form solution is derived for the climb phase to the cruise altitude. Practical feasibility is demonstrated on a microcontroller-based onboard computer, with execution times analyzed for flight software compatibility. The robustness of the proposed framework is validated via high-fidelity hardware-in-the-loop tests for two distinct scenarios: a multi-phase cruise mission and a short-range ballistic trajectory subject to propulsion uncertainties. Results confirm high precision and accurate impact angles across vastly different flight regimes, ranging from low-altitude cruise to high-dynamic reentry. Full article

The dynamics of pulsed laser ablation plumes strongly influence thin-film deposition quality; however, pressure-dependent collision accumulation and component-resolved transport in binary metal plumes remain poorly understood. In this study, a kinetic-statistical model was employed to investigate the propagation of an Al_0.75Ti_0.25 plume in a low-pressure inert Ar background at a laser fluence of 8 J/cm². The results show that, at t = 0.56 μs, the cumulative number of particles that have experienced at least one collision increases with pressure in the range of 0.001–1 Pa and follows an approximately power-law dependence. Across the entire pressure range and throughout the 0.08–0.56 μs interval, the collision fraction of Ti remains consistently higher than that of Al. Based on a Ti-normalized cumulative collision index, the propagation regime can be classified into a near-free-flight region, a transition region, and a collision-influenced region, with only minor temporal variations in the corresponding boundary pressures. Further analysis of the initial velocity spectrum shows that Ti contributes more strongly to the high-velocity tail, which explains its greater propensity for collision during propagation. These findings provide a quantitative framework for understanding pressure-dependent collision accumulation and species transport in binary metal plumes under inert low-pressure conditions. Full article

This study aims to improve the accuracy of cruise-phase power consumption prediction for multirotor unmanned aerial vehicles operating under varying wind conditions. Existing parametric energy models typically retain the wind velocity vector in the ground or inertial reference frame, and this representation does not distinguish between axial drag contributions along the fuselage and lateral attitude-correction contributions perpendicular to it. The proposed framework addresses this limitation through a physics-informed coordinate transformation that projects the measured wind vector into the body frame of the aircraft using quaternion-derived heading angles, yielding separate axial and lateral wind components. These components enter the power model as two additional predictors that augment the induced-power baseline, with the axial term following a cubic airspeed–power relationship consistent with parasitic drag formulations and the lateral term following a quadratic relationship consistent with attitude-correction mechanics. The framework is validated on a publicly available flight dataset, which comprises 188 flights of a DJI Matrice 100 quadcopter across payloads of 0 to 0.75 kg, ground speeds of 4 to 12 m/s, and altitudes of 25 to 100 m. Compared with the induced-power baseline, the proposed model reduces the root mean square error by 15.9% and the mean squared error by 29.7% during the cruise phase. The improvement is larger when wind speeds exceed 6 m/s, a regime in which the baseline residuals increase while the proposed model retains a comparatively stable error profile. Residual analysis indicates that baseline errors follow an approximately quadratic trend relative to the axial and lateral wind components, consistent with established parasitic-power and attitude-correction formulations. The closed-form structure of the proposed model is compatible with onboard execution on flight controllers, which suggests a feasible pathway toward its use as the power-prediction module within downstream range-estimation and energy-reserve sizing routines. Full article