High-Resolution Direction Of Arrival Estimation Based On Sparsity Theoiy

Restricted by variety of factors, the aperture of the antenna array can not be largeenough, which results in the wider main lobe and higher side lobe level of the pattern.Meanwhile, the resolution of the Radar is too low to distinguish the spatially adjacenttargets. The higher resolution of orientation can be obtained through the progressingrapidly theory: Compressed Sensing, which makes full use of the priori information ofsparsity with fewer sensors. In allusion to three kinds of array systems (Uniform LearArray, planar array and Bistatic MIMO radar), the application of sparsity theory inestimating the bearing of the targets is discussed in detail.Owing to the vast number of the sensors and the complexity of constructingtwo-dimension basis, row-column synthesis technique is applied to estimate thetwo-dimension position of the targets in planar. Therefor, the problem oftwo-dimensionally union localization of the targets can be transformed into twoone-dimensional angular estimations, and then the azimuth and elevate of the sourcescan be acquired respectively. The simulation has prove the higher resolution broughtby the proposed algorithm.For the sake of estimating the DOD-DOA (Direction of Department–Direction ofArrival) of the targets in Bistatic MIMO radar more precisely, a new reweighted1norm constrained model is activated with its reweighting method altered based on theconventional reweighted1norm constrained model. The proposed algorithm willhave better effect of anti-boise. Besides, large amount of simulations wereimplemented to demonstrate the feasibility and the effective noise-suppression of thealgorithm.