A reduced dimension multiple signal classification–based direct location algorithm with dense arrays
Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. Based on the idea of dimension reduction, the algorithm avoids multi-dimensional search in spatial...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-05-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/15501329221097583 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Aiming at the issue of parameter matching in conventional two-step location, a reduced dimension multiple signal classification direct position determination algorithm based on multi-array is proposed. Based on the idea of dimension reduction, the algorithm avoids multi-dimensional search in spatial domain and attenuation coefficient domain and reduces the search complexity. Simulation results show that the performance of the algorithm is better than the traditional angle of arrival two-step localization algorithm and subspace data fusion direct localization algorithm. |
|---|---|
| ISSN: | 1550-1477 |