Codes for "Source Localization for Sparse Array using Nonnegative Sparse Bayesian Learning"

The main codes of the paper published in Signal Processing

This work is to address the problem of source localization for sparse arrays, by formulating a nonnegative sparse signal recovery (SSR) problem and developing a nonnegative sparse Bayesian learning (NNSBL) algorithm.
1. The proposed algorithm is given in 'NNSBL.m', and the conventional SBL algorithm is given in 'Conven_SBL.m' for comparison.
2. 'MRA_output.m' is used to generate the array output data, and 'Peaksearch.m' and 'peak_find.m' are used to find the locations of the peaks in the spatial spectrum.
3. 'Main_Simulation.m' is used to display the spatial spectrum.
4. 'rmse_snr.m' is used to display the RMSE of DOA estimation versus SNR.
5. 'rmse_snapshot.m' is used to display the RMSE of DOA estimation versus the number of snapshots.