Millimeter Wave Real-Time Tracking and Imaging of Moving Objects Based on Virtual MIMO Array and State Vector Prediction

Abstract

Millimeter wave imaging systems are being rapidly applied to indoor security, industrial nondestructive evaluation and automotive radar systems. Millimeter wave real-time imaging is the ultimate goal of many applications. However, in order to achieve high resolution, the current real-time imaging system needs to integrate a large number of transceiver antennas, which has high hardware complexity and high cost. In addition, there are few researches on the imaging and tracking solutions of moving targets in current millimeter wave imaging. The combination of spatial point cloud mapping imaging technology and virtual MIMO array is a good compromise to achieve short time and low complexity. Therefore, this paper proposes a high-speed point cloud tracking imaging algorithm based on virtual array and target state vector prediction. Through the configuration of the virtual array, the reflection data of the target is processed and the space vector and the state vector of the target is determined. Kalman filter is used to predict and track the target point cloud. In this paper, a $3\times 4$ virtual MIMO array is used to test the proposed method. The experimental results show that the proposed method can rapidly image and continuously track moving human objects with a delay time of 100 ms, and the predicted target movement trajectory error is less than 15 cm.

Keywords

• Millimeter wave (MMW)
• virtual MIMO array
• real-time imaging
• point cloud