Collaborative forward‐looking imaging and reconnaissance technology for manned/unmanned aerial vehicles. Issue 19 (9th August 2019)

• Record Type: Journal Article
• Authors: Meng, Ziqiang; Li, Xiaoming; Lu, Chengjun; Zhu, Daiyin
• Is Part Of: Journal of engineering. Volume 2019:Issue 19(2019)
• Page Start: 6117
• Page End: 6121
• Publication Date: 2019-08-09
• Subjects: autonomous aerial vehicles -- minimisation -- synthetic aperture radar -- radar imaging -- Doppler radar -- remotely operated vehicles; reconnaissance technology -- imaging advantage -- synthetic aperture radar -- unmanned aerial vehicle -- high‐resolution imaging -- complicated space‐variance property -- traditional mono‐static SAR -- novel‐phase space‐variance correction method -- imaging focus performance; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2019.0299
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : 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.