Adaptive Matrix Information Geometry Detector With Local Metric Tensor

Hao, Wu; Cheng, Yongqiang; Chen, Xixi; Li, Xiang; Wang, Hongqiang

doi:10.1109/tsp.2022.3189179

Cited by 14 publications

(2 citation statements)

References 48 publications

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“…Recently, related studies on radar target detection methods based on information geometry received a lot of attention for their distinct advantages in hetero-clutter environments [32][33][34][35][36][37][38][39][40][41][42][43][44]. Specifically, the matrix information geometry (MIG) detector, which was pioneered by Barbaresco [45] and developed by Cheng et al [46], shows a novel detection scheme for target detection.…”

Section: Introductionmentioning

confidence: 99%

A Steering-Vector-Based Matrix Information Geometry Method for Space–Time Adaptive Detection in Heterogeneous Environments

Zou,

Cheng,

et al. 2024

Remote Sensing

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Plagued by heterogeneous clutter, it is a serious challenge for airborne radars to detect low-altitude, weak targets. To overcome this problem, a novel matrix information geometry detector for airborne multi-channel radar is proposed in this paper. The proposed detector applies the given steering vector and array structure information to the matrix information geometry detection method so that it can be used for space–time adaptive detection. While improving the detection performance, the matrix information geometry detector’s original anti-clutter advantage is enhanced as well. The simulation experiment results indicate that the proposed detector has advantages in several of the properties related to space–time adaptive detection, while its computational complexity does not increase significantly. Moreover, experiment results based on the measured data verify the superior performance of the proposed method. Sea-detecting data-sharing-program data, mountaintop data, and phased-array radar data are employed to verify the performance advantage of the proposed method in heterogeneous clutter and the ability for weak target detection.

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Section: Introductionmentioning

confidence: 99%

A Steering-Vector-Based Matrix Information Geometry Method for Space–Time Adaptive Detection in Heterogeneous Environments

Zou,

Cheng,

et al. 2024

Remote Sensing

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“…In [25], the Toeplitz structure is constrained to the SCM by using the geometric method of alternate projections. In [26][27][28], the application of information geometry-based CCM estimation methods to target detection problems is systematically investigated. The above research demonstrates that geometric methods can accurately estimate the CCM with small sample support.…”

Section: Introductionmentioning

confidence: 99%

Estimation of clutter covariance matrix in stap based on knowledge-aided and geometric methods

Jing,

Du,

Tian

et al. 2023

Phys. Scr.

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The insufficient number of available samples can cause inaccurate estimation of the clutter covariance matrix (CCM) in space-time adaptive processing (STAP), resulting in degraded clutter suppression performance. To tackle this problem, a CCM estimation approach based on knowledge aided and geometric methods is proposed in this paper. A combination of environmental as well as structural (Persymmetric or Symmetric structure) knowledge information is utilized to model the covariance matrix of each sample as a knowledge-aided Hermitian positive definite (KAHPD) covariance matrix. The estimation problem is introduced into the Riemannian manifold composed of the KA-HPD covariance matrices, and the geometric method is used for nonlinear processing. Based on the Kullback-Leibler (KL) divergence and the KL mean, the final estimated CCM is designed as a weighted combination of each KA-HPD covariance matrix. Experiment results show that the two designed structural covariance matrix estimators possess superior clutter suppression performance.

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Spectrum sensing in uncalibrated MIMO-based cognitive radios

Mohammadi,

Zaimbashi

2024

Digital Signal Processing

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Adaptive Matrix Information Geometry Detector With Local Metric Tensor

Cited by 14 publications

References 48 publications

A Steering-Vector-Based Matrix Information Geometry Method for Space–Time Adaptive Detection in Heterogeneous Environments

A Steering-Vector-Based Matrix Information Geometry Method for Space–Time Adaptive Detection in Heterogeneous Environments

Estimation of clutter covariance matrix in stap based on knowledge-aided and geometric methods

Spectrum sensing in uncalibrated MIMO-based cognitive radios

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