Open AccessCollaborative forward‐looking imaging and reconnaissance technology for manned/unmanned aerial vehicles
Author(s) -
Meng Ziqiang,
Li Xiaoming,
Lu Chengjun,
Zhu Daiyin
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0299
Subject(s) - computer science , computer vision , remote sensing , synthetic aperture radar , artificial intelligence , property (philosophy) , geology , philosophy , epistemology
With the imaging advantage of bistatic forward‐looking synthetic aperture radar, collaborative forward‐looking imaging and reconnaissance technology for manned/unmanned aerial vehicles could be performed, in which unmanned aerial vehicle can realise two‐dimensional (2‐D) and high‐resolution imaging and further attacking targets in its straight‐ahead position. However, there exists more complicated space‐variance property in this special configuration than traditional mono‐static SAR. Such property will lead to performance deterioration of imaging if not corrected effectively. To address this problem, 2‐D frequency spectrum with high precision is first obtained based on squint minimisation method here, and then a novel‐phase space‐variance correction method is developed through polynomial fitting. Imaging focus performance on targets could be improved significantly with authors’ method. Several simulations for scattering targets confirm its validity.