I did a Google search on that phrase from your post, and got lots of useful hits. Have a look at the hit list to see if you can find what you are looking for:tomography said:tomographic image resolutions from wifi sensing
Tomographic imaging using WiFi sensing is a technique that leverages WiFi signals to create detailed images of an environment. By analyzing the changes in WiFi signal strength and phase as they pass through different objects, it is possible to reconstruct a 2D or 3D representation of the space, similar to how medical tomography works but using radio waves instead of X-rays.
WiFi sensing improves image resolution by utilizing the high frequency and widespread availability of WiFi signals. Multiple WiFi transmitters and receivers can be strategically placed around the environment to capture a large amount of signal data from various angles. Advanced algorithms then process this data to enhance the spatial resolution and accuracy of the reconstructed images.
The key challenges include dealing with signal noise and interference, accurately modeling the propagation of WiFi signals through different materials, and ensuring sufficient spatial coverage and diversity of signal paths. Additionally, computational complexity and the need for robust algorithms to process large datasets are significant hurdles.
Common algorithms used for reconstructing images from WiFi signals include Compressed Sensing, Backprojection, and various Machine Learning techniques. These algorithms help in interpreting the signal variations and converting them into high-resolution images by solving inverse problems and optimizing the reconstruction process.
Yes, WiFi-based tomographic imaging can be used in real-time applications, although it requires efficient data processing and fast algorithms to achieve real-time performance. Advances in computational power and algorithm optimization have made it feasible to use this technology in applications such as security monitoring, indoor navigation, and smart home automation, where real-time imaging is crucial.