Investigating acousto-optic modulation techniques to enhance LiDAR range resolution by refining signal timing and frequency control, enabling sub-millimeter precision in distance measurement for advanced sensing applications.

Exploring novel acousto-optic interactions to achieve dynamic and high-speed beam steering in LiDAR systems, facilitating non-mechanical laser deflection for improved adaptability in autonomous navigation and environmental mapping.

1. Develop a radar detection system utilizing spintronic sensors for enhanced microwave detection and positioning accuracy.
2. Demonstrate the capabilities of the spintronic radar system through simulations and experimental validations.
3. Fabricate and Test Microwave-Spintronics-based Radar detection, frequency identification, and position localisation.
4. Explore the feasibility of integrating spintronic radar sensors into existing radar systems or developing standalone spintronic radar units.
5. Investigate potential applications of the spintronic radar system in areas such as surveillance, autonomous navigation, and target tracking.

An FL-based underwater lidar image classification system ensuring an adversarially robust functioning environment. It is mainly applicable to lightweight underwater navigation systems with limited computational capabilities. It utilizes a set of underwater lightweight devices as data generators and training locations, and a separate on-land base station acts as the aggregator. In addition, the onsite training of the model leads lesser bandwidth for data transfer.

About the Technology: Capturing Technology – UAV Technology.

The project represents a significant advancement in mapping technology by leveraging cutting-edge UAV  and LiDAR sensors to conduct aerial mapping. This technological approach enhances the accuracy of topographic data collection, enabling precise and efficient mapping.