We spent some time this week reviewing the feedback from our project proposal and ensuring that our project scope was well-defined, including constraining our use-case to static devices in an indoors environment, but also adding the requirement that we be able to distinguish multiple devices physically close to each other. These are already requirements that we had in mind, so the main change is just documenting them properly. As a result, there are no added costs or schedule changes.
We were able to test the CSI data produced by the AX200 wifi card using PicoScenes, and saw that moving the device around / moving ourselves in front of the antenna would affect the measured signal-strength and phase data; so we know that we are able to get meaningful measurements. We also verified that we are able to get individual signal-strength data from each antenna, which is useful for verifying
The main risk we are worried about is whether the fidelity of our data (in terms of noise and quantization) will be high enough to get the level of accuracy we want. Our contingency is based on the fact that we have a variety of different measurements which we are fusing together, so we’re expecting that with all the data combined, we’ll be able to get sufficient accuracy and meet our 1m requirement.
The main principles of engineering we’ve been using so far include electromagnetism and RF (in terms of choosing antennas and the considerations of multipath propagation); signal processing (interpreting the data we get from the wifi card, phase-difference-of-arrival, etc.); and some probability/statistics (in implementing the filtering algorithm to deal with noise in our measurements).
Below image shows our current experiments using an open-source dataset (“Intel Open Wi-Fi RTT Dataset“) of time-of-flight data between client devices and access-points, and attempting to find the location of the APs using this data.
