Research On High Resolution And Interference Cancellation Of Sparse Array

The bigger the aperture of antenna arrays, the stronger of arrays’directivity. For theuniform linear arrays, the method of increasing the number of elements or increasingelements’ distance of the ULA can achieve the aim of increasing aperture. However,increasing the number of elements will make the system more complex, and there mayappear big lobe when elements’ distance is too large. The number of elements of sparsearrays is smaller, and its elements’ distance is larger, so sparse arrays can make thesystem more simple, and its lobe is low. Using sparse arrays to increase aperture canmeet high demand of radar system. This paper adopts characters of sparse arrays.First, the theory of the multiplication of antenna arrays’ directional diagram is thebasic of researching arrays, so this theory is introduced in the first time. To evaluate thedirectional diagram of sparse array, there gives several methods to judge whether it isgood or not. The judgments are side-lobe level and main-lobe width. The paperintroduces the mathematical model of uniform linear arrays and sparse arrays. Ultimatetheory of DOA is introduced. In this part, the way to evaluate the ability of the DOA ofsparse arrays, like concepts of resolving power is introduced.Second, this paper researches the best distribution of sparse array. When theaperture of antenna arrays and the number of elements are fixed, the number ofdistribution of sparse array is countless. How to distribute the array and get the lowestside-lobe level is the foundation of researching sparse array. Three algorithms are usedto get the lowest side-lobe level. Essential operations, the definitions and steps of thethree algorithms are introduced. Three algorithms are used for the synthesis of sparsearray. The premises of simulation are involved with several kinds: the number of arrayis odd or even; the elements are symmetrical or not. Comparing the level of side-lobeafter using three algorithms, we can get the best synthesis of sparse array.Then, the paper analyses the ability of DOA of the best synthesis of sparse array weget in the second part. First, the theories and steps of the MUSIC algorithm arepresented here. Compared with uniform linear arrays, this paper analyses the superiorityof sparse array. The premises of simulation are involved with several kinds: the distanceof angles; the size of SNR; the sources are correlated or not. It provides a method toimprove the classic spatial smoothing algorithm used in ULA, thus the function can dealwith the correlated sources. This paper uses virtual array transformations to deal withthe correlated sources.Last, the paper analyses the interference cancellation ability of sparse array. Thispart is researched by anti-collision radar, which is one of the applications of sparse array. First working atmosphere of anti-collision radar is introduced. Thus we can get the typeand characteristics of interferences. This makes it clear that the interferences arecorrelated. Then an effective way to restrain interferences, ADBF is given, and we canget the weight vector in correlated situation. Simulating ADBF of sparse array, a lowestlevel may be appeared at the direction of interference. In this way, interferences can berestrained.