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Ethan’s status report for 04/29

This week I prepared for and did the final presentation. Other than that, I’ve been trying to work with one of the devices that we bought for which the pinging seemed to be not working with. Before the final demo, I will be working on getting the devices to work with our system, test the integrated system, and work on writing the paper and preparing for the demo.

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Thomas’s Status Report for 2/18

This week, I created the grid-based localization scheme we will use for finding these devices. Right now, it just adds a likelihood based on the time-of-flight of the devices, achieving about 5m of accuracy. We hope with the higher clock frequency of our AX200 board and the directionality we will have from the antennas, we’ll be able to improve even further. This puts us on schedule, and allows me to spend next week working on improving the localization system and handling the ToF measurement processing from the data in a more sophisticated way than we currently do it.

By next week, I hope to have localization accuracy improved to around 1.5m, and through a system that smooths the ToF better than the knowledge-of-the-crowd (averaging) we currently use.

I tested the implementation on an Intel RTT Dataset (Nir Dvorecki, Ofer Bar-Shalom, Leor Banin, Yuval Amizur, June 8, 2020, “Intel Open Wi-Fi RTT Dataset”, IEEE Dataport, doi: https://dx.doi.org/10.21227/h5c2-5439) and attached a picture below: top left is example output, bottom left is our system, the right-hand side is a visualization of what the likelihood function looks like.

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Thomas’s Status Report for 2/11

Good progress this week – I presented on Monday about our overall target and we got some excellent feedback from Professor Kim. We refined our use-case requirements and specified the MVP project a little more tightly afterward (less focused on sensing, more focused on IoT devices specifically). I am still conducting my literature review of WiFi localization and deciding which methods we will use. I still think the time-of-flight-based methods presented in WiPeep, expanded for multiple antennas, will be our best option. Next week I will start creating the actual MATLAB code to run for the processing.