This book focuses on sub-Nyquist sampling of ultra-wideband signals in aerospace systems, addressing the challenges of high sampling rates and massive data in spacecraft telemetry, star-carried radar, aerospace communication, remote sensing, and electronic reconnaissance, under constraints of limited space and load capacity. Based on FRI sampling theory, it studies sub-Nyquist techniques and parameter estimation for three common aerospace signal types. It first explores pulse sequence models with known and unknown waveforms, proposing multi-channel, spectrum expansion, and intelligent optimization-based FRI sampling methods. Then, extending FRI theory to the frequency domain, it develops two-channel cooperative structures to mitigate frequency ambiguity and aliasing for multi-frequency signals. Finally, for phase modulation signals widely used in aerospace communication and exploration, it proposes three FRI-based approaches for estimating key time-frequency parameters. Integrating theoretical derivations, simulations, and hardware implementations, this work represents the authors’ research achievements and serves as a valuable reference for scholars in aerospace, communication, and signal processing.

Zhiliang Wei (Member, IEEE), Doctor of Engineering. He is currently an associate researcher at the School of Electronics and Information Engineering, Harbin Institute of Technology. He has published more than 20 academic papers. His current research interests include intelligent information domain sampling, sparse signal processing, and automatic test technology.

Ning Fu (Member, IEEE) received the B.S., M.S., and Ph.D. degrees from the Harbin Institute of Technology (HIT), Harbin, China, in 2002, 2004, and 2009, respectively. He is currently a Full Professor with the School of Electronics and Information Engineering, HIT. His current research interests include information acquisition theory, finite rate of innovation sampling, compressive sensing, and automatic test technology.
 
Libao Deng (Member, IEEE) received the B.Sc., M.Sc. and Ph.D. degrees from Harbin Institute of Technology (HIT), Harbin, China, in 2004, 2007 and 2012, respectively. He is currently a Full Professor with the School of Information Science and Engineering, HIT. His current research interests include multi/many-objective optimization, large-scale optimization, evolutionary algorithms and optimal scheduling.
 
Jingchao Zhang is currently a researcher with the School of Electronics and Information Engineering, Harbin Institute of Technology. His research interests include intelligent testing and equipment calibration. He has received various grants from National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, etc.