Millimeter wave radar sensor manufacturers indoor personnel detection and positioning module, millimeter wave radar is a new technology for indoor personnel detection and tracking in recent years. The principle is that electromagnetic signals are transmitted through the radar antenna, blocked by objects in the transmission path, and then the radar receives the antenna. The distance, speed and Angle of an object can be determined through a series of processing of the signals received.
In addition to millimeter wave radar sensors, indoor personnel detection and tracking sensors also include ultrasonic, passive infrared, active infrared (lidar, TOF) optical cameras and other sensors, but these sensors are easily affected by the external environment (such as light, temperature, etc.), resulting in virtual alarms. Millimeter wave radar sensor has all-weather characteristics, far superior to other sensors in environmental stability, and can meet the accuracy and stability requirements of indoor personnel detection. Therefore, the indoor personnel detection and positioning module of millimeter wave radar is increasingly used in security monitoring, smart home, smart pension and automatic door control and other fields. Millimeter wave radar has irreplaceable natural advantages in protecting personal privacy.
The indoor personnel detection, positioning module and tracking application of millimeter wave radar are developed based on 24GHz millimeter wave radar module and adopt FMCW, MIMO and other technologies, which have the advantages of high range accuracy, high speed accuracy, high Angle resolution and low virtual alarm rate. It can realize accurate detection, accurate positioning and stable tracking of indoor personnel, and effectively classify personnel and non-human objects. Count the number of people in the room, and steadily output information such as distance, speed and Angle. Millimeter wave radar sensor manufacturers detect and track in indoor environment personnel, eliminate static objects such as tables, chairs, walls, and can be accurately detected, accurately positioned and stably tracked at the same time.
Through the application of the indoor personnel detection and positioning module of millimeter wave radar, FMCW, MIMO static object elimination algorithm, multi-path interference elimination algorithm, group target tracking algorithm, human and non-human classification algorithm and other key algorithms are used to solve the problem of false targets caused by indoor multi-path, effectively classify human and other objects, and realize the function of multi-target tracking and positioning in indoor environment.
Static object elimination algorithm is mainly used to eliminate static objects in indoor environment (such as walls, tables and chairs, etc.). The algorithm involves signal processing module and data processing module, which can filter static objects by eliminating multiple puller channel targets and avoid the interference of static objects on moving targets. The multi-path interference elimination algorithm of millimeter wave radar sensor manufacturers is mainly used to eliminate false detection points brought by target movement in indoor scenes to avoid these false detection points being mistaken for targets by millimeter wave radar sensors for tracking output, resulting in false alarm problems. The algorithm will make a comprehensive judgment according to the indoor environment area and the original detection point information (such as distance, speed, Angle, signal-to-noise ratio, etc.) obtained by the millimeter-wave radar sensor to determine whether the original detection point is false, so as to filter out and greatly reduce the false alarm problem caused by multipath in indoor environment.
Indoor personnel detection and positioning module group target tracking algorithm is mainly used to accurately locate and stably track multiple moving targets in indoor environment. The algorithm firstly classifies the original detection points effectively and obtains different target clusters. Then the extended Kalman filter algorithm is used to track different clusters and obtain stable moving target traces.
The classification of human and non-human algorithm is mainly used to distinguish micro animals (such as rotating electric fans, floating curtains, etc.). Microfauna has a certain Doppler velocity which can easily lead to the misjudgment and tracking output of millimeter wave radar sensor. Human and non-human classification algorithm counts the features of human and micro-animals, extracts effective features, carries out target classification, and outputs only the tracking results of human.
