Current Issue : October-December Volume : 2026 Issue Number : 4 Articles : 5 Articles
As critical air-dropped acoustic sensors for underwater target detection, sonobuoys are frequently compromised by severe hydrodynamic self-noise induced by sea-surface wave excitation, which masks target signals and degrades detection performance. While structural optimizations have traditionally been employed, effective signal-processing-based noise suppression remains challenging because the noise is non-stationary and physically coupled with buoy motion. To address the limited physical interpretability of conventional decomposition methods, this study proposes a physically guided self-noise suppression framework: VMD Constrained by DCCA Correlation (VMD-DCCA). The main contribution is the incorporation of the Detrended Cross-Correlation Analysis (DCCA) coefficient between the sonobuoy’s vertical velocity and the acoustic data as a correlation-dependent constraint within the Variational Mode Decomposition (VMD) optimization process. This motion prior allows more targeted isolation of motion-induced components than standard data-driven decomposition. Simulation and controlled water-tank results show that VMD-DCCA outperforms EEMD and standard VMD, achieving an SNR improvement of approximately 15 dB at an input SNR of -9 dB. The reconstructed signal also preserves visible narrowband spectral lines in the time-frequency representation. These results demonstrate the potential of the proposed method for controlled or post-processing sonobuoy self-noise reduction, while validation under irregular open-ocean conditions remains necessary....
Automatic modulation recognition has been recognized as an effective technique for noncooperative communication and intelligent transmission. In this paper, we propose a new lightweight method for automatic modulation recognition, aiming to extract crucial discriminative features of signals for higher recognition accuracy while reducing spatial costs. To enhance the dissimilarity between samples, this paper combines an improved attention block and convolutional operations with the recurrent neural network, focusing on key features during the training phase to efficiently differentiate signal sequences. By replacing standard convolutions with depthwise separable convolutions, the model’s computational complexity is reduced while enhancing its feature extraction capability. Furthermore, the method incorporates pruning to reduce ineffective features, decreasing the model size while maintaining performance. Experimental results on RadioML2016.10a demonstrate that the proposed method outperforms other comparative methods, exhibiting both higher recognition accuracy and smaller model size. To validate real-world applicability, the algorithm was implemented on a software-defined radio platform for signal transmission and reception under practical conditions, achieving an accuracy of 87.22% in the presence of environmental noise, thus confirming its effectiveness in real-world scenarios....
This Technical Report presents a quantitative signal processing approach to analyze and correct eye drift during vestibulo-ocular reflex (VOR) measurements using the video Head Impulse Test (vHIT). The objective is to determine the extent of drift caused by goggle slippage—a technical artifact that can distort the VOR gain index. A total of 57 impulses were categorized into three protocols: Lateral, LARP, and RALP. For each impulse, peak head velocity and eye drift (estimated from the average velocity during the pre- and post-impulse rest periods) were extracted using a custom signal processing pipeline implemented in MATLAB R2020b and Python 3.11 64 bit. Results showed the highest drift in the RALP group (−7.41 deg/s) and the lowest in the LARP group (−3.08 deg/s). The correlation between head velocity and drift was most prominent in the RALP group (r > 0.7), highlighting the impact of stimulation direction on goggle stability. This study proposes a drift detection method to be integrated into VOR correction algorithms, thereby enhancing gain analysis and saccade detection in automated systems....
Addressing the challenges of electromagnetic compatibility testing and non-destructive inspection of internal structures in miniaturized electronic devices. This paper reports a non-destructive testing method based on wide-field imaging using diamond nitrogenvacancy (NV) centers, and systematically demonstrates its application on a black-epoxyencapsulated Universal Serial Bus (USB) flash drive. In the experiment, a swept microwave signal from 2.82 GHz to 2.97 GHz was sequentially injected into the four external interface pins of the USB drive. A bulk diamond served as the quantum sensing layer, and optically detected magnetic resonance (ODMR) was employed to perform wide-field imaging of the microwave field distribution on the surface of the signal lines within a 1 × 1 mm2 region of interest. The experimental results show that the microwave field distributions corresponding to different interface channels are significantly different. Based on these differences, the connection relationship between each signal line and its corresponding interface pin can be clearly identified, and the differences in field distribution as well as crosstalk characteristics among channels can be revealed. The method established in this work provides an effective technical pathway for non-destructive electromagnetic testing and functional verification of electronic products....
The reflection coefficient measurement of the RF signal generator output is clear when the signal generator output is turned off, as no interfering signal is present. However, measuring the reflection coefficient while the signal generator output is turned on creates complexity, as the generator’s output power can interfere with the reflected signal. A vector network analyzer (VNA) is the reference instrument for measuring the reflection coefficient, capturing both the magnitude and phase of scattering parameters. For measuring the active output of a signal generator, the signals created by the generator and the VNA must be isolated to prevent signal mixing and interference. This paper proposes a unique method to measure the output reflection coefficient of an RF signal generator when the output is on, using a VNA configured for one port reflection coefficient measurement. The method involves tuning the VNA receiver to a frequency slightly offset to the generator’s output. Simultaneously, selecting a narrow intermediate frequency bandwidth (IFBW) reduces the receiver’s noise floor and also eliminates out-of-band interference. As a result, the VNA and the generator operate in different frequency bands to avoid interferences between them, enabling accurate magnitude and phase measurements. To automate the process, a Windows-based software has been developed. This software automates the measurement sequence, controls generator power levels and VNA sweep parameters, captures both the magnitude and phase of the reflection coefficient, and records the result data. It also supports measurement at different output power levels, enabling characterization across a wide range of operating conditions....
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