Super resolution direction finding technique of vortex electromagnetic wave radar in missing mode

Abstract

Vortex electromagnetic waves have superior performance over electromagnetic waves. In order to improve the radar super-resolution lateralization technique in its missing modes, this study proposes to start from the perspective of mode missing. The missing modes are reconstructed using the Adaptive Step Size Gradient Descent (ASSGD) method by exploiting the features of the missing modes. The linear minimum mean square error (LMMSE) estimation method is also used to solve the problem of poor reconstruction accuracy due to the Missing Modes. The Missing Modes Iterative Adaptive Approach (MMIAA) algorithm and Missing Modes Sparse Learning via Iterative Minimization (MMSLIM) algorithm are then used. Minimization (MMSLIM) algorithm to recover missing modes. The results showed that the RMSEs of the recovery errors of MMSLIM, MMIAA and ASSGD were 0.16, 0.31 and 0.82 respectively at a modal missing ratio of 0.7, while ASSGD fails to recover the missing modal data at a modal missing ratio of 0.9. The overall data quality of the azimuthally estimated RMSE was average when the signal-to-noise ratio was at [–5, 10] dB. And the curve becomes flatter when it reaches 15 dB or more, indicating that MMSLIM, MMIAA has important theoretical and practical value.