Cognitive FDA-MIMO radar for LPI transmit beamforming
- Author(s): Jie Xiong 1 ; Wen-Qin Wang 1 ; Can Cui 2 ; Kuandong Gao 3
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View affiliations
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Affiliations:
1:
School of Communication and Information Engineering , University of Electronic Science and Technology of China , Chengdu , People's Republic of China ;
2: School of Electronic and Optical Engineering , Nanjing University of Science and Technology , Nanjing , People's Republic of China ;
3: HUAWEI Technology Co., Ltd. , Chengdu , People's Republic of China
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Affiliations:
1:
School of Communication and Information Engineering , University of Electronic Science and Technology of China , Chengdu , People's Republic of China ;
- Source:
Volume 11, Issue 10,
October
2017,
p.
1574 – 1580
DOI: 10.1049/iet-rsn.2016.0551 , Print ISSN 1751-8784, Online ISSN 1751-8792
Active radar is vulnerable to illegal eavesdroppers due to its high-gain beam-scanning signals. To reduce active radar visibility and enhance its low probability of intercept (LPI) capability, this study proposes a cognitive LPI transmit beamforming scheme using frequency diverse array (FDA) and multiple-input multiple-output (MIMO) hybrid array antenna. The achievement of LPI is due to the unique range-angle-dependent transmitting beampattern of FDA-MIMO radar, which minimises the beam power at the target location to reduce its visibility and simultaneously maximise the power at the radar receiver without degrading the radar detection performance. Furthermore, the FDA-MIMO radar operates in a cognitive way: the receiver estimates the target range and the direction of arrival with a two-dimensional multiple signal classification algorithm, and feedbacks their estimates to the transmitter to update the FDA-MIMO transmit beamforming. As the transmit beamforming optimisation is non-convex problem, the authors propose three methods, namely linear combination, non-linear combination and closed form solution. All the proposed methods are verified by simulation results.
Inspec keywords: transmitting antennas; signal classification; radar signal processing; radar antennas; antenna radiation patterns; concave programming; probability; radar receivers; radar detection; array signal processing; MIMO radar
Other keywords: direction of arrival estimation; nonlinear combination; nonconvex optimisation; radar detection performance; two-dimensional multiple signal classification algorithm; cognitive FDA-MIMO radar; illegal eavesdroppers; transmit beamforming optimisation; linear combination; frequency diverse array; target range estimation; LPI capability; closed form solution; high-gain beamscanning signals; low probability of intercept capability; cognitive LPI transmit beamforming; range-angle-dependent transmitting beampattern; beam power minimisation; radar receiver; FDA; active radar visibility reduction; multiple-input multiple-output hybrid array antenna
Subjects: Antenna arrays; Other topics in statistics; Radar equipment, systems and applications; Optimisation techniques; Signal processing and detection
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