UAV Target Detection Algorithm Using GNSS-Based Bistatic Radar

Author(s):  
Hong-cheng Zeng ◽  
Hao-jie Zhang ◽  
Jie Chen ◽  
Wei Yang
2019 ◽  
Vol 19 (1) ◽  
pp. 116-132
Author(s):  
Hristo Kabakchiev ◽  
Ivan Garvanov ◽  
Vera Behar ◽  
Dorina Kabakchieva ◽  
Kalin Kabakchiev ◽  
...  

Abstract The paper offers new application of a Multi-channel Forward Scatter Radar (MFSR), which uses GPS signals for detection of air targets on their GPS radio shadows. The multi-channel GPS MFSR detector consists of several channels, which process information from several satellites simultaneously. The phenomena of diffraction in the near area is used for shadow target detection. The target is considered to be detected, if it is detected at least in one of detector channels. Two experiments have been made to verify the proposed detection algorithm. The results obtained show that the proposed multi-channel detection algorithm can be successfully used for detection of low-flying air targets at very short distances or the near area of diffraction. Such targets are undetectable in GPS bistatic radar.


Author(s):  
Dinghe Wang Dinghe Wang ◽  
Qinglong Bao Qinglong Bao ◽  
Zhaodong Niu Zhaodong Niu ◽  
Zengping Chen Zengping Chen

2021 ◽  
Vol 13 (4) ◽  
pp. 701 ◽  
Author(s):  
Binbin Wang ◽  
Hao Cha ◽  
Zibo Zhou ◽  
Bin Tian

Clutter cancellation and long time integration are two vital steps for global navigation satellite system (GNSS)-based bistatic radar target detection. The former eliminates the influence of direct and multipath signals on the target detection performance, and the latter improves the radar detection range. In this paper, the extensive cancellation algorithm (ECA), which projects the surveillance channel signal in the subspace orthogonal to the clutter subspace, is first applied in GNSS-based bistatic radar. As a result, the clutter has been removed from the surveillance channel effectively. For long time integration, a modified version of the Fourier transform (FT), called long-time integration Fourier transform (LIFT), is proposed to obtain a high coherent processing gain. Relative acceleration (RA) is defined to describe the Doppler variation results from the motion of the target and long integration time. With the estimated RA, the Doppler frequency shift compensation is carried out in the LIFT. This method achieves a better and robust detection performance when comparing with the traditional coherent integration method. The simulation results demonstrate the effectiveness and advantages of the proposed processing method.


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