Research On Joint Estimation Method Of Frequency And DOA Based On CRT Reconstruction Algorithm

With the rapid development of array signal processing technology,in the fields of radar,sonar,electronic countermeasures,wireless communication,etc.,the high precision estimation of the frequency and the direction of arrival(DOA)of the signal are playing an increasingly important role.When the signal operating frequency of the application is high,if the sampling in the time domain satisfies the traditional Nyquist theorem,not only in some cases,the hardware system is difficult to implement,but also a large amount of sampling data will reduce the processing speed of the system.To satisfy the array element spacing greater than half wavelength in the airspace,the mutual coupling phenomenon between the array elements will also reduce the accuracy of the parameter estimation or even the algorithm.Therefore,it is an urgent research direction to perform high precision parameter estimation of the sample sequence obtained after under sampling the signal.The under sampling in the time domain and the large-array spacing in the spatial domain will bring the problem of spectral blur and phase ambiguity respectively.In the face of an increasingly complex electromagnetic environment,it is not enough to estimate the parameters of a single incident signal.At the same time,when multiple target signals arrive at the array,the relationship between the spectrum information,the phase information and the target signal is blurred,and the unknown problem is caused.This paper focuses on these issues and proposes a solution based on the Chinese remainder theorem(CRT)reconstruction algorithm.Firstly,the basic theory of the Chinese remainder theorem is summarized.Because of its ambiguity solution characteristics,it can be introduced into the array signal processing under under sampling.However,since the traditional Chinese remainder theorem reconstruction algorithm is sensitive to the residual error,it adopts the stubbornness.The Chinese remainder theorem estimates the target signal.For the case where multiple target signals arrive at the array,a solution to the frequency estimation based on the multi-integer robust Chinese remainder theorem reconstruction algorithm is proposed.Then,a frequency estimation CRT model of multiple target signals under time domain under sampling is established,and multiple parallel under sampling is performed,and a plurality of fuzzy frequency remainders obtained by each sample is used to construct afrequency remainder of each channel,combining multiple integer stubborns.The Chinese Residual Theorem reconstruction algorithm performs frequency estimation of multi-target signals in a certain frequency range.In addition,an improved interpolation DFT frequency estimation algorithm is introduced to correct the spectral peak position,which reduces the frequency residual error and improves the frequency estimation accuracy.Finally,a group matching method of multi-target signal arrival array phase values in space is proposed.The DOA estimation problem of multi-target signals is transformed into multiple independent single-target DOA estimation problems.The DOA is used to estimate the CRT model and the robust CRT.The reconstruction algorithm completes the DOA estimation of multi-target signals,and completes the DOA estimation of the condition that the array element spacing is larger than half wavelength,which greatly improves the error range of the phase difference measurement allowed by the algorithm.At the same time,a model for improving the joint estimation of frequency and DOA is established.The interpolation DFT frequency estimation algorithm is used to correct the frequency offset fraction and phase to value,and then the exact frequency remainder and phase difference remainder of the signal is obtained by the same sample sequence,so as to improve the efficiency of the sample.The frequency and DOA unambiguous joint estimation of multi-target signals of arbitrary amplitude in space is completed with less algorithmic computation.Simulation experiments to verify the effectiveness,robustness performance of the joint estimation algorithm.