THz Radar

THz Radar - About the project

Based on our research work in past ten years where we worked on processing of radar signals and implementations of various radar system for Earth’s surface observation, we will in this research project upgrade knowledge with radar in Tera-Hertz (THz) band. Observation of surfaces and structures of objects has huge practical potential in field of safety, quality of goods and materials which cannot be observed with bare eye. Also this technology is able to improve quality of life with implementation in medicine for human tissue observation. Modern technologies are capable to detect micro cracks in materials and sense materials behind walls and under clothes. Medicine desire application where is possible to remote measure of life function of patient, like breathing and heart

biting. Some of this function it is possible to sense with low price equipment. This research area is very interesting and rapid developing, since the necessary equipment for the implementation of THz radar became affordable. In collaboration with Laboratory for Electro Optics and sensor on the UM-FERI systems we have ability to implement such THz radar system. The idea is to transfer knowledge from generation and focusing SAR data in the THz field and also investigation and implementation of THz radar. We will examine the device for generating and receiving of THz signals. Here we see the contribution in designing THz radar using micro-processing of optical fibres technology and laser diode controlling in order to generate THz waves. THz radar will be used for three-dimensional (3D) tomography. Our research may later turn in applications to detect various gas admixtures, detections of cancer cells and implementation of THz camera for physical phenomena observation.

Thera are two project objective. The first is to investigate the most appropriate today available technology for THz radar implementation. Here we will focus on innovative approaches for THz waves generation. The second objective of the research project is the analysis of the interaction of THz waves with different objects and to lay the foundations for the processing of THz waves, which will be used in future real applications. In this research project we will first design laboratory THz radar prototype. The radar will be based on a similar principle as the interaction of the optical signal with the photo conductive antenna. This can be achieved by using the micro-processing of optical fibres and laser diodes controlling. Current state of the art in this field reveals that it is impossible to generate any shape of THz waves. In the research project, we will propose a special way of control the laser diode with which will be possible to change the frequency of the THz signal and thus affect the shape of the output signal, which is needed to implement the THz radar with synthetic aperture. In this section, we will investigate principles of generating a chirp signal using of laser and laser diode and observe the shape of the received signal on receiving photo conductive antennas. Here we propose antenna arrays in THz band for generating THz signals. With antenna arrays we will produce directional waves. Also we will deal with radar techniques for generating and receiving a signal, such are Spotlight, Stripmap and Stearing modes. Antenna arrays are also important for the reception of signals because it can simulate movable radar platforms and thus can replace movable radars.

We will also develop algorithms for focusing SAR images and algorithms for the visualization of received signals. We will propose two methods, measuring of received signal strength and measuring of Time of Flight (ToF) and in this way enable of 3D visualization of objects. We will be using the technique SAR, where we will develop algorithms to automatically identify the type of data and the type of surface. We will propose techniques of interferometry for the detection of changes in materials and on surface of materials.

The last part of the project introduces a use of complex valued convolutional networks for THz data recognition. The emphasis will be on proposing operators for complex valued convolutional network and develop learning algorithms. Our recent internal findings showed that the complex valued approach can improve recognition rate for more than 10% in very noisy environments.

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