Zhao Z.-G.,Key Research Laboratory of Wuhan Radar Academy |
Chen J.-W.,Key Research Laboratory of Wuhan Radar Academy |
Bao Z.,Key Research Laboratory of Wuhan Radar Academy
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | Year: 2012
The ocean clutter is one of the significant factors that limit the detection performance of the over-the-horizon radar (OTHR) system for slowly moving ship targets. Aimed at the problem that when the Doppler of a target is not significant to allow discrimination in Doppler, the target peak can be spilt or deviate from the true position, a modified eigen-value decomposition (MEVD) approach, which combines the moving target indication (MTI) and an adaptive approach based on eigen-value decomposition is adopted. In MEVD approach, the clutter near target is suppressed with MTI and other clutters are suppressed with adaptive approach. Meanwhile, this approach is able to suppress not only the first order but also high order ocean clutter, so the signal-to-clutter-plus-noise ratio is increased, which helps to improve detection performance of OTHR. Theoretical analysis and the results of simulations and real data processing indicate the effectiveness of MEVD approach.
Hui C.,Key Research Laboratory of Wuhan Radar Academy |
Hui C.,National the National Information Control Laboratory |
Yao W.,Key Research Laboratory of Wuhan Radar Academy |
Yao W.,National the National Information Control Laboratory |
And 2 more authors.
Applied Mechanics and Materials | Year: 2012
A self-calibration algorithm for concentric uniform circular arrays (C-UCA) in the presence of mutual coupling is presented. The proposed algorithm can simultaneously estimate the directions of arrival (DOA) of signal sources and coupling coefficients of antenna array with a calibration source. It not only can calibrate the mutual coupling of the inner sub-arrays, but also can compensate for the mutual coupling between sub-arrays. Compared with conventional self-calibration algorithm based on iterative alternating minimization technique, the proposed algorithm transforms joint estimation about DOA and mutual coupling coefficients into cascaded estimation, which means that the parameters can be obtained by one dimensional spectrum peak search. The proposed self-calibration algorithm has high estimation precision and low computational burden. Simulation results show the effectiveness of the presented method.