168 citations
- University of Science and Technology of ChinaCN4 papers
- National University of Defense TechnologyCN3 papers
- Beijing Institute of TechnologyCN1 paper
- China Electronics Technology Group CorporationCN1 paper
- Keio UniversityJP1 paper
- Naval University of EngineeringCN1 paper
- Tsinghua UniversityCN1 paper
- Wuhan Institute of TechnologyCN1 paper
6 papers
Adaptive Subspace Signal Detection and Performance Analysis in Nonzero-Mean Clutter
Weijian Liu, Zhenyu Xu, Jun Liu +2
To solve the problem of detecting subspace signals in nonzero-mean clutter, we propose adaptive detectors, based on the strategies of generalized likelihood ratio test (GLRT), Rao…
Bayesian Rao test for distributed target detection in interference and noise with limited training data
Daipeng Xiao, Weijian Liu, Jun Liu +3
This paper has studied the problem of detecting a range-spread target in interference and noise when the number of training data is limited. The interference is located within a ce…
Adaptive radar detection of subspace-based distributed target in power heterogeneous clutter
Daipeng Xiao, Weijian Liu, Jun Liu +3
This paper investigates the problem of adaptive detection of distributed targets in power heterogeneous clutter. In the considered scenario, all the data share the identical struct…
LDA-MIG Detectors for Maritime Targets in Nonhomogeneous Sea Clutter
Xiaoqiang Hua, Linyu Peng, Weijian Liu +4
This paper deals with the problem of detecting maritime targets embedded in nonhomogeneous sea clutter, where limited number of secondary data is available due to the heterogeneity…
Detector Design and Performance Analysis for Target Detection in Subspace Interference
Weijian Liu, Jun Liu, Tao Liu +2
It is often difficult to obtain sufficient training data for adaptive signal detection, which is required to calculate the unknown noise covariance matrix. Additionally, interferen…
Local-set-based Graph Signal Reconstruction
Xiaohan Wang, Pengfei Liu, Yuantao Gu
Signal processing on graph is attracting more and more attentions. For a graph signal in the low-frequency subspace, the missing data associated with unsampled vertices can be reco…