Multiple moving sources passive location based on multiset canonical correlation analysis

To solve the problem of multiple moving sources passive location,a novel blind source separation(BSS) algorithm based on the multiset canonical correlation analysis(MCCA) is presented by exploiting the different temporal structure of uncorrelated source signals first,and then on the basis of this algorithm,a novel multiple moving sources passive location method is proposed using time difference of arrival(TDOA) and frequency difference of arrival(FDOA) measurements.The key technique of this location method is TDOA and FDOA joint estimation,which is based on BSS.By blindly separating mixed signals from multiple moving sources,the multiple sources location problem can be translated to each source location in turn,and the effect of interference and noise can also be removed.The simulation results illustrate that the performance of the MCCA algorithm is very good with relatively light computation burden,and the location algorithm is relatively simple and effective.

To solve the problem of multiple moving sources passive location, a novel blind source separa- tion （BSS） algorithm based on the muhiset canonical correlation analysis （MCCA） is presented by exploiting the different temporal structure of uncorrelated source signals first, and then on the basis of this algorithm, a novel multiple moving sources passive location method is proposed using time difference of arrival （TDOA） and frequency difference of arrival （FDOA） measurements. The key technique of this location method is TDOA and FDOA joint estimation, which is based on BSS. By blindly separating mixed signals from multiple moving sources, the multiple sources location problem can be translated to each source location in turn, and the effect of interference and noise can also he removed. The simulation results illustrate that the performance of the MCCA algorithm is very good with relatively light computation burden, and the location algorithm is relatively simple and effective.