Research On Improvement Of Coprime Array And Direction Of Arrival Estimation

The Direction of Arrival(DOA)estimation is an important branch in the field of array signal processing,which is widely used in radar,sonar,radio astronomy,navigation,and wireless communications.Array design makes an important impact on DOA estimation performance.Compared with uniform linear array,sparse arrays can obtain higher angular resolution and more degree of freedom under the same physical sensors.Therefore,how to use limited physical sensors to improve target resolution performance has become a hot issue for array signal processing research.We take the coprime array as the research object and propose novel sparse arrays with a high degree of freedom.The main work includes:1.We first analyze the structure of the thinned coprime array and the influence of specific elements on the difference coarray.By investigating the relationship between the physical sensors and the virtual positions,then we derive the mathematical expression of the hole position.The above conclusions provide the theoretical conditions for the following sparse array designs.2.By moving the element at the 0 position to the set position,we propose an improved structure of the thinned coprime array.While keeping the number of sensors unchanged,the consecutive lags in the difference coarray are increased.In particular,the mathematical expressions of the proposed array related to the consecutive lags and the degree of freedom are derived.Simulation Experiments verify the effectiveness of the proposed array.3.Considering the movement of the subarray and relocation of the specific sensor of the thinned coprime array,a novel sparse array is proposed.We move one of the subarrays of the original thinned coprime array to the negative coordinates and the reference sensor to the specific position,obtaining longer consecutive lags.Further,the mathematical expression about the consecutive lags is derived.Simulation experiments demonstrate the effectiveness of the proposed array.