With the rapid development of technologies such as satellites and rockets, we start to communicate and exchange information between ground and space and explore space information world. In the process of information exchange, undoubtedly, a large amount of analog signals need to be digitized for information encoding, communication, and storage. Therefore, new sampling methods have become the key technology to realizing the above process, especially in exploring wideband, high dynamic range unknown signals in space. Sensing and recognition of spatial information will become a key technology for exploring space and future space travel.
The researchdirection focuses on the theory and methods of space information sensing, signal recognition, and localization. Specific research areas: compressed sensing and machine learning, wideband and high dynamic range electromagnetic signal detection, wide-area distributed multi-satellite collaborative sensing, efficient extraction and classification of spectrum situational information, and fusion and mining of multi-source spectrum big data. It intersects and integrates with disciplines such as physics and astronomy to establish new sensing theories and methods.
Device description：
The device is an integrated solution for high-speed signal acquisition. It can directly sample 2GHz broadband analog signals, with customized RF modules, use compressed sensing algorithm for signal processing, and display the sampling effect through the software interface. The equipment can be used in satellite signal measurement, development of multi-mode 6G base station, phased array radar, automation equipment, medical imaging and spectrum detector and many other fields.
Software introduction:
Fast and accurate recovery of 950-2150MHz (1.2GHz bandwidth) RF broadband signal, time domain and frequency domain display.
Collection control: multi-channel selection function, run prompt function, data collection refresh rate setting function, and cycle running time prompt function.
Data saving: Supports single triggering and continuous saving, and supports user-defined storage path and number of files saved.
Algorithm implementation:
The signal is collected directly in the compressed way, and the advanced compressed sensing technology is used to decompress the signal, thus greatly reducing the sampling cost. The compressed sampling and demodulation of DVB-S2 satellite signals are realized, which can identify satellite signals accurately and efficiently.
It is equipped with intelligent recognition signal modulation algorithm based on artificial intelligence neural network technology, which can accurately identify signal modulation mode from a small amount of data collection.
