FFT samples to covert to range domain.Break vector of samples into a 2D matrix of Chirp vs.De-interleave Channel 1 -2 and I/Q samples.The data that has been shared as part of this challenge was created by the following flow of processing: These individual gesture actions have varying matrix sizes hence a cell data format was used to create a ragged data cube. Afterwards, the raw data was then cut into individual gestures that occurred over the whole period. It was then initiated to capture 30 seconds of data and the candidate repeated the actions numerous times within this window. It was set up on a lab bench at the same height as the gesture action. The system we have used has one transmit antenna and two receive antennas (only one was used for the purposes of this dataset). The Ancortek Radar system used to generate the dataset is a 24 GHz FMCW radar that has a standalone GUI to control and capture data or can be commanded within a Matlab interface to capture signals. The data is then stored in this format in order for it to be read in, features to be extracted and the classification process to be performed.
The data itself has been pre-processed so that the signatures have been cut into individual actions from a long data stream, filtered to enhance the desired components and processed to produce the Doppler vs. This database includes signals from 4 different types (Wave / Pinch / Click / Swipe). A database of gestures has been created and uploaded here using the Ancortek Radar system. In order to evaluate how effective a radar is in recognising gestures, this challenge provides data that can be used to apply classification methods. Some examples of gestures are Wave / Pinch / Click / Swipe. This research challenge proposes the use of a compact Radar sensor as a device that can be used in HMI and has encouraged researchers to investigate the feasibility of a radar device in this roll. Recently Google has developed a small radar sensor call Soli which is proposed as a device for gesture recognition. This includes the Microsoft Kinetic Sensor, Virtual Reality wand controllers and even sensors that read your brainwaves. There has been a vast amount of research into various technologies used as human-machine interfaces (HMI). The focus on this data challenge is the classification of 4 separate hand gestures. The data generated for this classification challenge was created using an Ancortek 24 GHz FMCW radar a 750 MHz bandwidth, more details about the radar system can be seen in the table below: This is then mixed with the received signal in order to obtain the range/Doppler of a target. This constantly transmits a Chirp, which is a signal that increases (up-chirp) or decreases (down-chirp) its frequency linearly with time. The image below shows an example plot of a micro-Doppler signature of a person walking towards a radar.Ī typical short-range radar system architecture is the Frequency Modulated Continuous Wave (FMCW) radar. This movement creates a signature which was coined as Micro-Doppler by researcher V. For example, a person may walk forwards at 3 m/s but as they move at this speed their arms and legs oscillate back and forth.
All of this analysis used the phenomenon called Micro-Doppler which is the additional movements a target has on top of its bulk velocity.
Radar sensors have previously been successfully used to classify different actions such as walking, carrying an item, discriminating between people and animals gaits or drones and bird targets. If you make a publication that uses DopNet or the Data, and you want to add it on the Publications and Articles Page, contact us. If you want to read Publications and Articles relating the Micro-Doppler Gesture Recognition or Radar Research, they are available in the Publications and Articles Page.
#NET RADAR ANTENNA DOWNLOAD#
It can be obtained here: Data Information and Download Links The Data is available to universities and scientific bodies for use in their research. Furthermore, it started as a Laidlaw Scholarship project.
Francesco Fioranelli ( Delft University of Technology (TU Delft), Delft, Netherlands). Matthew Ritchie ( University College London (UCL), London, United Kingdom) and Richard Capraru ( Nanyang Technological University (NTU) and Singapore Agency for Science, Technology and Research (A*STAR), Singapore) within the UCL Radar Research Group in collaboration with Dr.
#NET RADAR ANTENNA SOFTWARE#
The data here was measured with FMCW and CW Radars.ĭopNet‘s structure makes it a useful tool for Machine Learning Gesture Recognition software and Image Processing for the spectrograms. What is DopNet? View on GitHub What is DopNet?ĭopNet is a large Radar database organised in a hierarchy in which each node represents the data of a person which is divided into different gestures recorded from that person. What is DopNet? | DopNet Skip to the content.
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