A5100776726- Advanced SAR Imaging Techniques
- Wireless Signal Modulation Classification
- Radar Systems and Signal Processing
- Optical Systems and Laser Technology
- Digital Media Forensic Detection
- Target Tracking and Data Fusion in Sensor Networks
- Sparse and Compressive Sensing Techniques
- Speech and Audio Processing
- Blind Source Separation Techniques
- Image and Signal Denoising Methods
- Advanced Measurement and Detection Methods
- Antenna Design and Optimization
- Underwater Acoustics Research
- GNSS positioning and interference
- Gait Recognition and Analysis
National University of Defense Technology
2020-2024
Air Force Engineering University
2014-2022
Specific emitter identification is a technique that distinguishes different emitters using radio fingerprints. Feature extraction and classifier selection are critical factors affecting SEI performance. In this paper, we propose an method the Bispectrum-Radon transform (BRT) hybrid deep model. We BRT to characterize unintentional modulation of pulses due superiority bispectrum distributions in characterizing nonlinear features signals. then apply model based on denoising autoencoders belief...
Synthetic Aperture Radar (SAR) is a high-resolution imaging sensor commonly mounted on platforms such as airplanes and satellites for widespread use. In complex electromagnetic environments, radio frequency interference (RFI) severely degrades the quality of SAR images due to its widely varying bandwidth numerous unknown emission sources. Although traditional deep learning-based methods have achieved remarkable results by directly processing visual ones, there still considerable room...
Exploiting the time different of arrival to passive detection is becoming a promising issue in surveillance. Time can resolve location target by using difference from multi-base station same radar wave beam. The that base stations are not beam rarely studied. This paper puts forward asynchronous and builds critical area solve problem which Critical relative all just right wave. By further analyzing this area, Euclidean distances aircraft obtained used information arrival. What more, analysis...
The sparse representation using time-frequency atoms is a useful analysis method for radar signal processing. Based on Time-Frequency theory, can match signals and represent it sparsely. Traditional atomic dictionary only the linear frequency modulation signal, while novel proposed in this paper not properly but also non-linear relationship appropriately. It because that has sinusoidal factor which improves atoms' ability to signals. Compared with traditional dictionaries, simulation result...
Information fusion is an important step in cooperative reconnaissance signal processing, which can be divided into three types: data-level, feature-level and decision-level fusion. Data-level has the advantage of information completeness but large data volume makes it hard to apply practically. Based on sparse representation intercepted correlations between signals, a data-level algorithm proposed. In algorithm, expressed compressed for communication. Then fuse coefficients based them. The...
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Radar radiator signal recognition is a key component of electronic reconnaissance system. In order to improve the accuracy low probability interception(LPI) under condition signal-to-noise ratio, this paper proposes an algorithm for feature extraction and in high-order spectral transform domain. This method overcomes shortcomings previous algorithms that rely heavily on experience cannot adapt waveform changes. First, bispectral transformation used form three-dimensional physical...