Moving Target Detection Algorithm Based on Millimeter-Wave OFDM Radar

The emergence of Integrated Sensing and Commu-nications (ISAC) technology becomes increasingly indispensable as the convergence between the physical and virtual realms advances. The OFDM radar system, as one of the ISAC ap-plications, has received widespread attention, which not only enables efficient communication but also realizes a variety of sensing applications. Target detection, as a crucial application in sensing, involves identifying targets' position and motion status, constituting critical steps in the process. This paper focuses on the joint estimation of delay and Doppler frequency within the OFDM radar system. We use a super-resolution algorithm based on compressed sensing to estimate the channel parameters, including delay and Doppler frequency. The high dimensionality of the dictionary matrix in the super-resolution algorithm results in an increase in computational complexity. To solve it, we take advantage of the differentiability of L2-norm, which is applied in the Iterative Shrinkage Thresholding Algorithm (ISTA) to optimize. And then we construct a prototype using a millimeter wave system to validate our proposed method. Field tests have been conducted to validate the accuracy of delay and Doppler frequency estimation for moving objects, showcasing a significant reduction in computational complexity through the utilization of the proposed algorithm. These findings contribute to the development ISAC technique by providing empirical evidence supporting the effectiveness and efficiency of the suggested approach.