Unmanned Aerial Vehicle Recognition Based on Clustering by Fast Search and Find of Density Peaks (CFSFDP) with Polarimetric Decomposition

Abstract

Unmanned aerial vehicles (UAV) have become vital targets in civilian and military fields. However, the polarization characteristics are rarely studied. This paper studies the polarization property of UAVs via the fusion of three polarimetric decomposition methods. A novel algorithm is presented to classify and recognize UAVs automatically which includes a clustering method proposed in “Science”, one of the top journals in academia. Firstly, the selection of the imaging algorithm ensures the quality of the radar images. Secondly, local geometrical structures of UAVs can be extracted based on Pauli, Krogager, and Cameron polarimetric decomposition. Finally, the proposed algorithm with clustering by fast search and find of density peaks (CFSFDP) has been demonstrated to be better than the original methods under the various noise conditions with the fusion of three polarimetric decomposition methods.

Special Issue on “Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement”

“…After a very careful peer-review process, a total of 32 papers were accepted. These works include SAR/ISAR [2][3][4][5][6][7][8][9], polarimetry [10][11][12], MIMO [13,14], direction of arrival (DOA)/direction of departure (DOD) [13][14][15], sparse sensing [5,14,16], ground-penetrating radar (GPR) [17][18][19], through-wall radar [20,21], coherent integration [22,23], clutter suppression [24,25], and meta-materials, among others [26][27][28][29][30][31]. All of these accepted papers are the latest research results and are expected to be further advanced, applied, and diverted.…”

A Novel Density Peak Fuzzy Clustering Algorithm for Moving Vehicles Using Traffic Radar

“…The SDPFC algorithm proposed in this paper is characterized by the idea of using quadratic clustering to correct clustering results. The cluster center of each cluster and the number of clusters are obtained by the initial clustering algorithm based on the density peak [43]. Then, the clustering result of the initial cluster is corrected by the fuzzy clustering algorithm based on the spindle update, and the final clustering result is obtained.…”

Applying Polarimetric Target Decomposition to 2D Turntable ISAR Imagery of a Complex Vehicle

“…In the literature, a few studies have dealt with polarimetric ISAR (Pol-ISAR) signatures of radar targets [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26].…”

“…Simulation implementation may also be a good representative of a practical situation. As an example, in [24], the numerical data of an unmanned aerial vehicle (UAV) were used in conjunction with a fusion of coherent decomposition. In [25,26], the turntable ISAR data of a T-72 tank target [27] were analyzed via Pauli decomposition.…”