The widespread use of unmanned aerial vehicles (UAVs) has introduced significant security challenges, including unauthorised intrusions and privacy breaches. Conventional identification methods, such as radar and visual surveillance, often struggle to accurately distinguish between different UAV types or individual devices, limiting their effectiveness in countering these threats. To address these concerns, an enhanced empirical mode decomposition method has been developed. This method employs the Welch algorithm to extract power spectral density (PSD) features, which are then used to form the radio frequency fingerprint (RFF). Finally, a statistical classifier is employed to recognise and classify UAVs. The results of experimental studies indicate that this technique yields an average precision of 97% in binary classification (drone vs. no drone) and 84.7% in quaternary classifications (identifying four drone models). A comprehensive performance evaluation, conducted using confusion matrices and receiver operating characteristic (ROC) curves, demonstrates that the classifier performs well across all categories, with low misclassification rates.

In this article, a qualitative work has been carried out based on airborne pulsed Doppler (PD) RF sensor consist of its operational requirements in terms of phase noise modeling and associated contributing factors. Precise and efficient theoretical modeling of phase noise requirement for airborne-PD radar or long-range RF sensor is presented. This work also emphasis on the limitation of conventional phase noise modeling practices used for PD RF sensor. An improved equation has been derived for accurate phase noise estimation considering the range correlation effect and inline flicker contribution on residual phase noise requirement. Random vibrations causes increase in phase noise level around low frequency offsets region in local oscillator. The proposed phase noise model is efficient enough to counter phase noise degradation at lower frequency offsets. The proposed model is also experimentally validated. Improved modeling offers benefit in reducing the stringent RF sensor phase noise specifications at close-in frequency offsets using range correlation effect and precise inclusion of inline flicker contribution. Present work can be used to mitigate random vibration effects at close-in phase noise offsets, which avoids complex stabilization practices and stringent oscillator design phase noise specification.

The purpose of this paper is to disclose improved crystal based frequency source system covering design techniques and experimental methodologies for the stabilization of phase noise performance of X-band phase-locked loop (PLL) at 10.6 GHz. Phase noise performance of PLL-based unit under test (UUT) is prone to disturbance occurred in random vibration profile frequency spectrum. UUT self-resonance plays vital role in occurrence of disturbance in random vibration profile. The stabilization of phase noise performance during dynamic (random) vibration condition is achieved by following methodologies, i.e. vibration-isolator compensation techniques, purification tactic for reference crystal of PLL, and spatial location analysis for finding out mounting position of reference crystal. Spatial analysis helps to filter out UUT self-resonance frequency from random vibration spectrum which leads to reduction of frequency resonance pickups during random vibration testing.

The combustion instability characteristics in a model dump combustor with an exhaust nozzle were experimentally investigated. The first objective was to understand the effects of operating conditions and geometric conditions on combustion instability. The second objective was to examine more generalised parameters that affect the onset of combustion instability. Three different premixed gases consisting of air and hydrocarbon fuels (C2H4, C2H6, C3H8) were burnt in the dump combustor at various inlet velocity, equivalence ratio and combustion chamber length. Dynamic pressure transducer and photomultiplier tube with a bandpass filter were used to measure pressure fluctuation and CH* chemiluminescence data. Peak frequencies and their maximum power spectral densities of pressure fluctuations at same equivalence ratios showed different trends for each fuel. However, the dynamic combustion characteristics of pressure fluctuations displayed consistent results under similar characteristics chemistry times regardless of the used hydrocarbon fuels. The results showed that characteristic chemistry time and characteristic convection time influenced combustion instabilities. It was found that the convective-acoustic combustion instability could be prevented by increasing the characteristic chemistry time and characteristic convection time.

We analyze the fluctuations in the X-ray flux of 20 AGN (mainly Seyfert 1 galaxies) monitored by RXTE and XMM-Newton with a sampling frequency ranging from hours to years, using structure function (SF) analysis. We derive SFs over four orders of magnitude in the time domain (0.03-300 days). Most objects show a characteristic time scale, where the SF flattens or changes slope. For 10 objects with published power-spectral density (PSD) the break time scales in the SF and PSD are similar and show a good correlation. We also find a significant correlation between the SF timescale and the mass of the central black hole, determined for most objects by reverberation mapping.

Global Navigation Satellite Systems (GNSS) Doppler measurements are commonly used for velocity-based relative positioning and aiding Inertial Navigation Systems (INS) in signal degraded environments. The aim of this paper is to characterise the Doppler measurements in GNSS harsh multipath environments. In multipath fading situations such as indoor and urban canyon environments, multipath components arrive to the receiver antenna from different paths and directions. These give rise to various Doppler shifts that cause errors in the velocity solution. In this work the Doppler measurements discrepancy characterised by Doppler spread in multipath environments is investigated. By assuming a ‘sphere of scatterers’ model and considering the antenna gain pattern, the theoretical Power Spectral Density (PSD) observed by a receiver is formulated. The theoretical findings are examined using two sets of measurements in dense multipath environments. Global Positioning System (GPS) live signals using non-isotropic antennas with different orientations are used for this purpose. Different motion directions are also examined using different data sets. An Assisted GPS (A-GPS) approach is utilised where the code phase and the navigation data bits are provided by a nearby outdoor antenna. By applying a ‘Block Processing’ technique, an epoch-by-epoch Doppler and velocity estimation is implemented. Herein, the Doppler and velocity measurements accuracy in addition to the Doppler spread characterization are studied. As shown both theoretically and experimentally, in harsh multipath environments the PSD of the observed signals is a function of the scatterers' geometry and the antenna gain pattern. The Doppler estimation accuracies in multipath and multipath-free cases are compared for different ranges of Carrier-to-Noise ratio (C/N0). Theoretical and experimental results revealed inaccurate Doppler estimation and poor Doppler-derived velocity solutions in dense multipath environments.