Name
Abstract | ||
|---|---|---|
This paper addresses the problem of direction finding for bistatic MIMO radar in the presence of unknown spatially colored noise. Taking the stationary property of the colored noise into consideration, a covariance differencing-based method is presented. The proposed method has computational complexity very close to that of ESPRIT. besides, it can suppress the colored noise without any virtual aperture loss. Therefore, it improves the accuracy of angle estimation compared with the existing de-noising algorithms. Numerical experiments are provided to examine the effectiveness and improvement of our algorithm. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICDSP.2018.8631628 | DSL |
Keywords | Field | DocType |
Covariance matrices,Estimation,Colored noise,Eigenvalues and eigenfunctions,Signal processing algorithms,MIMO radar,US Department of Defense | Aperture,Direction finding,Computer vision,Colors of noise,Computer science,Bistatic mimo radar,Artificial intelligence,Mimo radar,Signal processing algorithms,Covariance,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
1546-1874 | 978-1-5386-6811-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fangqing Wen | 1 | 68 | 13.81 |
| Xinyu Zhang | 2 | 24 | 12.48 |
| Fuzhou Yang | 3 | 0 | 0.34 |
| Zijing Zhang | 4 | 1 | 0.69 |