Multi-target Trajectory Tracking based on Interferometric FMCW Radar

What is it about?

Multiple human targets’ trajectory tracking is of great significance to radar based indoor monitoring and autonomous driving applications. Aiming at the difficulty that the targets’ movement information is hard to separate and match at various slow-time in radar echoes, a multi-target trajectory tracking method based on the Viterbi algorithm and interferometric radar system is proposed. In this work, the multi-target trajectory tracking is implemented using a one-transmitter and two-receiver frequency modulated continuous wave (FMCW) radar. Firstly, the fast Fourier transform (FFT) is applied to the fast-time and slow-time dimension of the FMCW radar echo separately so as to obtain the radial distance and velocity of the human targets. Secondly, interferometric processing is performed to the range-doppler series of the two receiving channels to obtain the azimuth degree of the targets, and thus two-dimensional coordinates. Then, the resulted trajectories are inputted into the Kalman filter to improve the trajectory tracking performance. Different from the existing work, this work employs both K-means clustering and Viterbi algorithm to process the motion information of multi-targets, realizing multi-targets separation, and thus achieving multi-target motion trajectory tracking purpose. The experimental results verify the effectiveness of the method.

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Why is it important?

The interference FMCW radar with one transmitter and two receivers was used in this work, reducing the complexity of the system. In addition, the K-means clustering and Viterbi algorithm were combined to process the motion information of multiple targets, achieving multi target separation and improving the accuracy of multi target tracking

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