Paper Info
Title
Multichannel Signal Modeling and AMTI Performance Analysis for Distributed Space-Based Radar Systems
Abstract
Due to the limited size, carrying capacity, power-aperture product, and high hardware cost of the satellite platform, the traditional single-platform spaceborne radar system encounters the problems of poor target minimum detectable velocity (MDV) performance, considerably deteriorating the moving target detection performance. To improve the air moving target indication (AMTI) performance, especially for a weak target, the distributed space-based radar system (DSBR) becomes a good candidate due to the longer along-track baseline (ATB) and spatial power synthesis. However, due to the sparse configuration of radar baseline distribution, the detection performance of air moving targets (AMTs) will be restricted by many practical factors in an actual DSBR system. In this article, multichannel signal models of an observed moving target and ground clutter are accurately established in a DSBR framework, where the error influences of cross-track baseline (CTB), terrain fluctuation, and channel inconsistency response are considered. Then, the influence of the nonideal factors, including the channel noise, long-intersatellite ATB, long-intersatellite CTB, synchronization errors, and interchannel amplitude and phase inconsistency errors, on the AMTI performance is analyzed term by term. The simulation results provide useful guidance for the system design of a DSBR with the AMTI tasks.
Year
DOI
Venue
2022
10.1109/TGRS.2022.3202567
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Keywords
DocType
Volume
Satellites, Spaceborne radar, Radar, Clutter, Radar antennas, Radar cross-sections, Radar clutter, Air moving target indication (AMTI), distributed space-based early warning radar, interchannel correlation analysis, space-time adaptive processing (STAP)
Journal
60
ISSN
Citations 
PageRank 
0196-2892
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Jiangyuan Chen100.68
Penghui Huang205.07
Xiang-gen Xia35167410.80
Junli Chen400.34
Yongyan Sun511.71
Xingzhao Liu619251.67
Guisheng Liao7996126.36