Geodesic Normal Coordinate-Based Manifold Filtering for Target Detection

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

doi:10.1109/tgrs.2022.3183432

Cited by 13 publications

(3 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…This type of detector does not require information on the statistical properties of the clutter background, but simply utilizes the geometry of the matrix manifolds. Experimental results show that the performance of such methods is significantly better than traditional methods in nonhomogeneous clutter [5]. Since the SAR image itself is a large rectangle, we construct the image blocks centered at each pixel point as Hermitian positive-definite (HPD) matrix manifolds.…”

Section: Introductionmentioning

confidence: 99%

Ship Detection in SAR Images via Kullback-Leibler Divergence-Based Matrix Information Geometry Detector

Xie

Cheng

2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Ship detection in synthetic aperture radar (SAR) imagery is an important application in the field of marine remote sensing. As the most common method in ship detection, classical constant false alarm rate (CFAR) methods rely on the target-to-clutter contrast and accurate estimates of distribution models, making it difficult to adapt to complex and variable sea surface backgrounds. Considering the limitations of the CFAR methods, this paper proposes a new detector for ship detection based on matrix information geometry (MIG) theory. The proposed detector models each SAR sample data as a Hermitian positive-definite (HPD) matrix, and uses the geometric mean of all HPD matrices corresponding to the background window to estimate the clutter, thus transforming the target detection problem into a measure of the Kullback-Leibler divergence (KLD) between two points on the matrix manifold. Different from the traditional CFAR detectors which use intensity information to differentiate between targets and clutter, the proposed detector utilizes the intrinsic geometry of the matrix manifold and employs KLD with good differentiation to measure the variance from targets to clutter.

show abstract

“…Another detection scheme is developed as the information geometry is applied to the statistical signal processing. Many geometrical measures, such as Riemannian distance, Kullback-Leibler divergence and so on, have made significant contributions to the detector design [18,19]. However, compared with GLRT, the complexity of the detection theorem based on the information geometry is extremely high.…”

Section: Introductionmentioning

confidence: 99%

Adaptive detection for resolvable multipath signal under heterogeneous clutter

Cao

Fan

et al. 2022

IET Radar Sonar & Navi

View full text Add to dashboard Cite

In the urban environment, the radar is easily affected by multipath (MP) returns. The problem of detecting point-like targets in the urban environment with the existence of resolvable MP returns under the background of heterogeneous clutter is addressed. Two adaptive detectors have been devised with a combination of prior information on the environment and echoes of target. The detectors can use the MP echoes in all MP prediction range cells for detection or in some available paths for signal detection by the available path selection algorithm that eliminates the weak signal propagation paths. Remarkably, the proposed decision schemes exhibit the desirable constant false alarm rate property with respect to the unknown parameters of the heterogeneous interference. The performance assessment, conducted on simulated data in terms of detection probability also in comparison with conventional solutions, highlights the effectiveness of the MP exploitation, while the MP signal is strong and shows the detection performance enhancement potential.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Geodesic Normal Coordinate-Based Manifold Filtering for Target Detection

Cited by 13 publications

References 29 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

Ship Detection in SAR Images via Kullback-Leibler Divergence-Based Matrix Information Geometry Detector

Adaptive detection for resolvable multipath signal under heterogeneous clutter

Contact Info

Product

Resources

About