TY  - JOUR
T1  - Hybrid-Level Fusion of Radar Imaging Methods
AU  - Onat, Emrah
AU  - Özkazanç, Yakup
PY  - 2025
DA  - October
Y2  - 2025
DO  - 10.26833/ijeg.1611426
JF  - International Journal of Engineering and Geosciences
JO  - IJEG
PB  - Murat YAKAR
WT  - DergiPark
SN  - 2548-0960
SP  - 1
EP  - 20
VL  - 11
IS  - 1
LA  - en
AB  - In this paper, hybrid-level fusion of radar imaging methods generally used in fighter aircraft such as Real Beam Ground Mapping (RBGM), Doppler Beam Sharpening (DBS) and Unfocused Synthetic Aperture Radar (SAR) is explained. Historically, these methods are improved based upon previously developed methods. These methods that are considered in this paper chronologically are investigated in terms of theoretical aspects in detailed. The primary distinction between the methods lies in their cross-range resolutions. However, it is not feasible to generalize the resolution comparison among the methods, as cross-range resolution is influenced by both fixed parameters; such as real antenna beam-width, and dynamic parameters; range, including the aircraft's speed and the angle of the radar beam. These varying factors contribute to the differences in resolution across methods. Because of their some disadvantages against each other, the new method which is the fusion of them is proposed in order to defeat these deficiencies. With the help of the fusion algorithm, a new image can be generated dynamically by using different radar imaging methods for each pixel of the image depending on the real antenna beam width, momentary range, beam position and aircraft speed. So, an image with better resolution can be produced by fusion of radar imaging methods than the image they would produce alone. The article provides details about the hybrid-level fusion algorithm discussed, including its application to a reference image. Both the individual methods and the fusion algorithm were executed for comparison. Additionally, the improved DBS algorithm was also implemented for benchmarking purposes. The final images generated by each method and the fusion algorithm are presented, and evaluation metrics such as Root Mean Square Error (RMSE), Peak Signal to Noise Ratio (PSNR) and Entropy (EN) were calculated to compare the results.
KW  - Remote Sensing
KW  - Radar Imaging
KW  - Real Beam Ground Mapping
KW  - Doppler Beam Sharpening
KW  - Synthetic Aperture Radar
KW  - Hybrid-Level Fusion
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UR  - https://doi.org/10.26833/ijeg.1611426
L1  - https://dergipark.org.tr/en/download/article-file/4484556
ER  -