People Counting Algorithms Based on IR-UWB Radar Sensors

In this dissertation, we propose people counting algorithms based on impulse radio-ultra wideband (IR-UWB) radar sensors. In detail, a people counting algorithm for counting the number of people in a certain area, and a bi-directional passing people counting algorithm for counting the number of people passing in each direction in a pathway or hallway are proposed. We also propose a multi-human detection algorithm that is the basis of these two different-purpose people counting algorithms. The multi-human detection algorithm is a signal processing algorithm for detecting valid signals among received signals of a radar. Conventional detection algorithms used in radar are algorithms for detecting target signals rather than noise signals. In contrast, the multi-human detection algorithms proposed in this dissertation can be used to detect more meaningful target signals among the multiple target signals received. In other words, we deal with the problem of which signals among multiple multipath signals reflected from people are regarded as valid signals. By using the proposed algorithm, it is possible to distinguish signals which are effective for determining the number of people among the signals in which the multipath signals from people are superpositioned. Based on the proposed multi-human detection algorithm, we propose a people counting algorithm to determine how many people are within the detection range of the radar. To do this, we statistically analyze signal patterns according to the number of people and distance distribution, and determine the number of people based on the maximum likelihood method. The bi-directional passing people counting algorithm is an algorithm that counts people moving in both directions from left to right or right to left in a wide passage or door. Based on two IR-UWB radar sensors, we generate new indicators to determine the number and direction of people passing in both directions and use it to determine the number and direction of people passing in each direction. We have implemented the multi-human detection algorithm, the people counting algorithm, and bi-directional passing people counting algorithm proposed in this dissertation using the commercial IR-UWB radar sensors. In order to verify the performance of the implemented algorithms, various scenarios were experimented and the experimental results are presented in the dissertation.Docto