The study of signal processing performance for simulation radar signals for drone-carrying ground penetrating radar
Abstract
The performance of underground object detections using ground penetrating radar (GPR) is critically dependent on the radar platform movement and its interaction with the ground under the area of surveillance. Conventional detection techniques of GPR rely on a parabolic shape of the radar signals generated on a GPR image, which restricts the radar movement such that the parabolic-shape image is properly generated; otherwise, the missed detection may occur. The limitation of radar platform movement further restricts the operations of the GPR under certain condition. For example, to use the GPR for improvised explosive device (IED) detection in a hostile environment, the radar platform movement is merely met the detection requirement by the parabolic-shape methods due to its speed changes during the course of the surveillance. A constant speed of the radar platform may inherit the risk of attacks by the oppositions. With recent advances in drone technologies and highspeed communications, carrying the GPR by drone is now possible. The drone-carrying GPR may reduce risks for the radar operators and can further extent the range of its operations or increase its capability to operate in an undesired environment, such as in a toxic environment, etc. However, since the drone maneuvering is nonlinear due to the facts of aerodynamics and wind conditions, the GPR images may suffer from the effects of such the drone movement. It is thus necessary to study the behavior of the drone platform maneuvering and its effects to GPR images and detection performance.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 20, 2022
- Source ID
- FA23861914035
Entities
People
- Akkarat Boonpoonga
Organizations
- Air Force Office of Scientific Research
- United States Air Force