Research And Implementation Of Correlation Interferometer Direction Finding Algorithm Based On Compressed Sensing And DOA Estimation

Radio direction finding,also known as Direction of Arrival(DOA)estimation,as one of the important research directions of array signal processing,and has been widely used in military and civilian fields.The traditional radio direction finding system mainly includes three methods: amplitude direction finding method,phase direction finding method and space spectrum estimation method.Facing the increasingly complex electromagnetic environment,the estimation performance of the classic direction finding algorithm drops sharply or even completely fails.The emergence of compressed sensing theory provides a new idea for radio direction finding.The combination of CS technology and radio direction finding technology can overcome many defects of traditional DOA estimation methods,so it has great scientific research value.The design goal of this project is to realize direction finding and monitoring of multi-target signals at the same time under large bandwidth,the main indicators of the system are as follows: the direction finding bandwidth is 20 MHz ? 8000 MHz,the system error below 2°,the sensitivity is within 20?V/m,and the direction finding time is within 5ms.In this thesis,firstly introduces Compressed Sensing theory,and intensive study the mathematical model of compressed sensing,including signal sparsity,observation and reconstruction.Then,the classical direction finding mechanism is introduced briefly.Secondly,the mathematical model of spatial spectrum estimation is analyzed,and two classical subspace class DOA estimation algorithms,MUSIC and ESPRIT are analyzed,focusing on the mathematical model of DOA estimation based on compressed sensing,and the reconstruction algorithm of DOA estimation based on compressed sensing includes greedy reconstruction algorithm and convex optimization reconstruction algorithm.Aiming at the problem that only single target signal can be detected by the current classical direction finding algorithm of correlation interferometer,a direction finding algorithm for correlation interferometer based on sparse reconstruction under a circular array model is proposed.The algorithm combines the compressed sensing technology with the classical correlation algorithm,uses the sample library of the classic algorithm as the sensing matrix,and uses the input signal as the observation vector,and uses the greedy algorithm to reconstruct the signal.Finally,the simulation results show that the performance of the proposed algorithm is better than the traditional algorithm.After the simulation verification,this algorithm is applied to the multi-channel interferometer direction finding system.Through the built test platform,test the conversion frequency and azimuth conversion of multiple target signals with known azimuth angle.The test results show that after using the improved correlation interferometer direction finding algorithm,the system accuracy of direction finding is 1.62°,the sensitivity is 18.1?V/m,and the direction finding time is 4.49 ms,and can carry out high precision direction finding on multiple target signals at the same time.The overall performance is better than traditional direction finding algorithms,which achieves the expected goal of this subject and has important engineering value.