Ideas for Radar Data Denoising and Fusion Based on Image Processing Techniques
- Resource Type
- Conference
- Authors
- Kitahara, Daichi; Wada, Yuuki; Mega, Tomoaki; Yoshikawa, Eiichi; Kikuchi, Hiroshi; Ushio, Tomoo
- Source
- 2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS) General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), 2023 XXXVth. :1-4 Aug, 2023
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
TV
Noise reduction
Distributed databases
Radar
Radar imaging
Attenuation
Minimization
- Language
- ISSN
- 2642-4339
We propose novel denoising and fusion schemes for radar data of distributed targets. To utilize established image processing techniques, we consider the denoising and fusion as image reconstruction in the Cartesian coordinates from the noisy data in the polar coordinates. We reconstruct the target image as the solution to a minimization problem with a regularization term. Denoising simulation in an attenuation correction scenario demonstrates the proposed scheme with the total variation regularization greatly reduces the noise.