Ultra-wide Bandwidth Radar Research Articles

Joint Motion Classification and Person Identification via Multitask Learning for Smart Homes

In a smart home environment, assisted living has been a topic of great research over the past decade. Human motion analysis is considered as a key technology for living states recognition in an assisted living system. Recent research has proved that rich information can be obtained from human movements, such as the motion category, moving patterns, and human identity. In this paper, a nonintrusive human movement sensing system is established with a mono-static ultrawide bandwidth radar. Then, we propose a well-designed joint motion classification (MCL) and person identification (PID) convolutional neural network (named as “JMI-CNN”). To recognize human motions and identities simultaneously, the network employs a multitask learning scheme as well as the attention mechanism and the hierarchical feature reuse strategies. We report the experimental result on the data from 15 individuals, each performing six motions. It shows that the model achieves a promising performance of 80.57% on the joint task, while the accuracy for MCL and PID are 98.50% and 80.92%, respectively. Moreover, we carry out ablation studies to evaluate the design principles of the proposed method. Discussions on the impact of signal noise ratio and slow-time window length are also conducted.

Through-Wall Multistatus Target Identification in Smart and Autonomous Systems With UWB Radar

Ultra-wideband (UWB) radar technology is a key technology in the field of target recognition, which is characterized by high resolution and strong anti-interference ability. In this paper, the ultra-wide bandwidth radar equipment is used to identify the multistatus human being after the brick wall by the fuzzy pattern recognition and genetic algorithm. First, The main characteristic parameters are selected and extracted from the received signal, and each feature parameters corresponding to a submembership function. Then, through the genetic algorithm to optimize the submembership function for constructing the membership function set. Last, According to fuzzy pattern recognition principle of maximum degree of membership function to establish target prediction function, and used MATLAB to carry on the simulation for it. The results show that the fuzzy pattern recognition can efficiently discern the multistatus human being behind the wall.

Radar Images of Leaks in Building Elements

Through leakage in the building envelope there is a penetration of air, water vapor and particles. The degree of leakage of air can be quantified by existing methods. However, the location of adventitious openings is often not known. In order to overcome the limitations in existing methods, a non-contact and non-destructive method based on ultra-wide bandwidth radar technology is suggested. A test-bed is designed that can measure with different polarization to be able to detect flaws in different directions. Initial measurements shows promising results for further development of the method of using radar images to find leaks in building elements.