Report

20195028

September 14, 2020 - September 20, 2020

Papers

Title 01:RF signal based drone detection using deep convolution neural network
Target : Summer intensive_2020

Title 02: RFDOANet: DOA Estimation of RF signal for UAV Localization based on Residual CNN.
Target : IEEE Signal processing letters

Title 03: Residual Convolution Neural Network for Drone Detection and Identification using RF Signal.
Target : Long Journal

Title 04: RF-Based UAV Surveillance System: A sequential Convolution Neural Network.
Target : ICTC-2020

Title 05: "Optimized Trickle Scheme for Low Power Lossy Network in Industrial Internet of Things".
Target : KICS Summer-2020

40% Progress
Last Week's Progress

Title 01:
- Complete the simulation result.
- Complete to write proposed model section.
- Complete the result discussion section.

Title 02:
- Receive the review comments and solve the issue of reviewrs

Title 03:
- study the related journal paper to make an efficient cost effective model.
- Simulate with the RF dataset.

Title 04:
- receive acceptance

This Week Todo's

Title 01:
- Revise the abstract and introduction section.
- Generate good quality simulation graph

Title 02:
- Modify the paper as the reviewer comments

Title 03:
- Finalize the Deep learning model.
- Test the model through dataset.

Title 04:
-Prepare the camera-ready copy.

Project Progress

Anti-drone project

40% Progress
Last Week's Project

Drone mode detection and Identification [Target]
- Study about the LABVIEW program

- Do some sample example simulation.

- Check the NI USRP 2921 for transmitting and receiving data.

This Week's Project

- Complete the total system configuration and test for the collection of RF data from drone.

- Configure the system for image and video based drone detection

- Collect task update from team member and report to prof

Monthly Goals

-Learn MATLAB, Machine learning and Artificial Intelligence, Python, LabView



- Complete one paper writing to submit in journal

Annual Goals

-At-least two SCI journal paper.

-At-least two International Conference