High-resolution, multi-frequency and full-polarization radar database of small and group targets in clutter environment

Hu, Cheng; Yan, Yujia; Wang, Rui; Jiang, Qi; Cai, Jiong; Li, Weidong

doi:10.1007/s11432-023-3889-7

Cited by 3 publications

(4 citation statements)

References 4 publications

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“…For more details about the radar system, see ref. [26]. The procedure of the experiment is described as follows.…”

Section: Phased Array Radar System and Setupmentioning

confidence: 99%

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Monitoring Dynamically Changing Migratory Flocks Using an Algebraic Graph Theory-Based Clustering Algorithm

Jiang,

Wang,

Zhang

et al. 2024

Remote Sensing

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Migration flocks have different forms, including single individuals, formations, and irregular clusters. The shape of a flock can change swiftly over time. The real-time clustering of multiple groups with different characteristics is crucial for the monitoring of dynamically changing migratory flocks. Traditional clustering algorithms need to set various prior parameters, including the number of groups, the number of nearest neighbors, or the minimum number of individuals. However, flocks may display complex group behaviors (splitting, combination, etc.), which complicate the choice and adjustment of the parameters. This paper uses a real-time clustering-based method that utilizes concepts from the algebraic graph theory. The connected graph is used to describe the spatial relationship between the targets. The similarity matrix is calculated, and the problem of group clustering is equivalent to the extraction of the partitioned matrices within. This method needs only one prior parameter (the similarity distance) and is adaptive to the group’s splitting and combination. Two modifications are proposed to reduce the computation burden. First, the similarity distance can be broadened to reduce the exponent of the similarity matrix. Second, the omni-directional measurements are divided into multiple sectors to reduce the dimension of the similarity matrix. Finally, the effectiveness of the proposed method is verified using the experimental results using real radar data.

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“…For more details about the radar system, see ref. [26]. The procedure of the experiment is described as follows.…”

Section: Phased Array Radar System and Setupmentioning

confidence: 99%

“…For more details about the radar system, see ref. [26]. After the synthesizing of the 10 stepped chirp pulses, a high-resolution range profile could be obtained.…”

Section: Phased Array Radar System and Setupmentioning

confidence: 99%

Monitoring Dynamically Changing Migratory Flocks Using an Algebraic Graph Theory-Based Clustering Algorithm

Jiang,

Wang,

Zhang

et al. 2024

Remote Sensing

Self Cite

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“…The first part is based on the sea-detecting data-sharing program (SDDSP) [57,58], and the second is based on the mountaintop data set to verify the robustness of the S-MIG detector, as shown in Section 4.2.2. The third one is an experiment based on the PHA radar data set published in [59] to investigate the weak target detection ability, as shown in Section 4.2.3.…”

Section: Experiments Based On Measured Datamentioning

confidence: 99%

“…In order to develop detection and tracking techniques, a series of low-altitude targets and radar clutter measurement trials were conducted by a high-resolution phased-array (PHA) radar in 2023 at Dongying, Shandong, China. The PHA radar is a Ku-band radar with a synthetic bandwidth of 1 GHz and detects targets from 300 to 2000 m. The PHA data set includes radar data for clutter measurement trails, migrating insect and bird observations, and drone observations [59].…”

Section: Real Data Of the Pha Radar Databasementioning

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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A Gaussian Mixture PHD Filter for Multitarget Tracking in Target-Dependent False Alarms

Jiang,

Wang,

et al. 2024

IEEE Trans. Aerosp. Electron. Syst.

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High-resolution, multi-frequency and full-polarization radar database of small and group targets in clutter environment

Cited by 3 publications

References 4 publications

Monitoring Dynamically Changing Migratory Flocks Using an Algebraic Graph Theory-Based Clustering Algorithm

Monitoring Dynamically Changing Migratory Flocks Using an Algebraic Graph Theory-Based Clustering Algorithm

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

A Gaussian Mixture PHD Filter for Multitarget Tracking in Target-Dependent False Alarms

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