Compressed Sensing Trilinear Model-based Angle Estimation for Bistatic MIMO radar
Xiaofei Zhang, Jianfeng Li, Ming Zhou, De Ben
Available Online March 2013.
- 10.2991/iccsee.2013.588How to use a DOI?
- Array signal processing, angle estimation, multiple-input multiple-output (MIMO) radar, trilinear model, Compressed Sensing.
In this paper, we address the transmit angle and receive angle estimation problem for a bistatic multiple-input multiple-output (MIMO) radar. This paper links MIMO radar angle estimation problem to the compressed sensing trilinear model. Exploiting this link, it derives a compressed sensing trilinear model-based angle estimation algorithm, which can obtain automatically paired two-dimensional angle estimation. The proposed algorithm requires no spectral peak searching or pair matching, and it has better angle estimation performance than conventional algorithms including estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Simulation results illustrate performance of the algorithm.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaofei Zhang AU - Jianfeng Li AU - Ming Zhou AU - De Ben PY - 2013/03 DA - 2013/03 TI - Compressed Sensing Trilinear Model-based Angle Estimation for Bistatic MIMO radar BT - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) PB - Atlantis Press SP - 2348 EP - 2352 SN - 1951-6851 UR - https://doi.org/10.2991/iccsee.2013.588 DO - 10.2991/iccsee.2013.588 ID - Zhang2013/03 ER -