TY - GEN
T1 - Joint Angle-Doppler Estimation for Passive Radar Based on Compressed Sensing
AU - Ni, Lijing
AU - Feng, Yuan
AU - Zhao, Juan
AU - Shan, Tao
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In this paper, a fast target angle and Doppler joint estimation method based on compressed sensing is proposed for passive radar. The joint estimation of multi-dimensional parameters enables improved resolution without introducing additional matching overhead. However, the dimension of the over-complete dictionary of multi-dimensional parameters is too large, resulting in a large computational complexity. In the proposed method, following segmented pulse compression, a multi-measurement vector model is constructed for the angle dimension, and then, a sparse representation model is formulated for the Doppler dimension to obtain the Doppler frequency of the targets. Additionally, the reconstruction algorithms are improved by using regularization operation. Simulated and experimental results demonstrate that the proposed method can accurately estimate both angle and Doppler parameters, while reducing the error term, reducing the dictionary dimension and achieving shorter running time.
AB - In this paper, a fast target angle and Doppler joint estimation method based on compressed sensing is proposed for passive radar. The joint estimation of multi-dimensional parameters enables improved resolution without introducing additional matching overhead. However, the dimension of the over-complete dictionary of multi-dimensional parameters is too large, resulting in a large computational complexity. In the proposed method, following segmented pulse compression, a multi-measurement vector model is constructed for the angle dimension, and then, a sparse representation model is formulated for the Doppler dimension to obtain the Doppler frequency of the targets. Additionally, the reconstruction algorithms are improved by using regularization operation. Simulated and experimental results demonstrate that the proposed method can accurately estimate both angle and Doppler parameters, while reducing the error term, reducing the dictionary dimension and achieving shorter running time.
KW - Compressed sensing
KW - extended orthogonal matching pursuit
KW - multi-parameter joint estimation
KW - passive radar
UR - http://www.scopus.com/pages/publications/105010818583
U2 - 10.1109/ISEAE64934.2025.11042070
DO - 10.1109/ISEAE64934.2025.11042070
M3 - Conference contribution
AN - SCOPUS:105010818583
T3 - 2025 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
SP - 1134
EP - 1139
BT - 2025 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Information Science, Electrical and Automation Engineering, ISEAE 2025
Y2 - 18 April 2025 through 20 April 2025
ER -