Target detection using space-time adaptive processing (STAP) and a multi-band, multi-channel software defined passive radar

2015 ◽  
Author(s):  
Mubashir Alam ◽  
Khalid Jamil ◽  
Sami M. Alhumaidi
Keyword(s):  
Target Detection ◽  
Space Time ◽  
Passive Radar ◽  
Adaptive Processing ◽  
Space Time Adaptive Processing ◽  
Multi Band

Space-Time Adaptive Processing Used for Underwater LFM and CW

2013 ◽  
Vol 313-314 ◽  
pp. 1229-1234
Author(s):  
Wei Lv ◽  
Zhi Jie Wang ◽  
Jian Chen Li ◽  
Ming Zhou Wang ◽  
Qiao Hu ◽  
...  
Keyword(s):  
Target Detection ◽  
Space Time ◽  
Adaptive Processing ◽  
Modulation Bandwidth ◽  
Steering Vector ◽  
Processing Gain ◽  
Space Time Adaptive Processing

In order to use the STAP in reverberation suppression, and compare the performances of STAP for underwater LFM with CW, the method of STAP used for LFM was proposed. Firstly, the principle of STAP for CW was analyzed, according to the underwater echo of CW. Then, the space-time steering vector of LFM is deduced by analysing the underwater echo of LFM. Fianlly, the performances of STAP for LFM and CW were compared by simulations. The results show that the proposed method of STAP for underwater LFM with narrower modulation bandwidth can achieve a better performance in target detection and estimate, and the processing gain of STAP for CW is higher than that of LFM form 1.6dB to 5.5dB with the modulation bandwidth from 100Hz to 600Hz.

scholarly journals An Application of the Orthogonal Matching Pursuit Algorithm in Space-Time Adaptive Processing

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3468 ◽  
Author(s):  
Anna Ślesicka ◽  
Adam Kawalec
Keyword(s):  
Target Detection ◽  
Matching Pursuit ◽  
Multiple Input Multiple Output ◽  
Radar Data ◽  
Space Time ◽  
Data Cube ◽  
Orthogonal Matching Pursuit ◽  
Adaptive Processing ◽  
Geometry Model ◽  
Space Time Adaptive Processing

The article presents a new space-time adaptive processing (STAP) method for target detection in a heterogeneous and non-stationary environment. In study it was proven that it is possible to estimate the clutter covariance matrix (CCM) in STAP by using the MIMO (Multiple Input Multiple Output) radar geometry model and the orthogonal matching pursuit (OMP) algorithm. For the estimation of spatio-temporal spectrum of clutter and target, a model of joint sparse recovery was established. As a result, clutter suppression and target detection in a heterogeneous environment will be achieved. In addition, the proposed method uses a single snapshot of the radar data cube, which eliminates the need for access to all training cells.

Sign in / Sign up

Export Citation Format

Share Document