This work confronts the complex issue of cross-interference in Frequency Modulated Continuous Wave (FMCW) radars, a critical concern that has become more pronounced with the proliferation of automotive radar systems. The study intro-duces a two-dimensional autoregressive (AR) modeling technique for signal reconstruction in the time domain, tailored specifically for the textured nature of FMCW radar frames composed of fast- time (Range bin) and slow-time (Doppler bin) signals. According to the simulations conducted in this study, the proposed 2-D AR model (of order 3) exhibits superior performance compared to its 1-D counterpart (of order 5). This is evidenced by a slightly lower Mean Absolute Percentage Error (MAPE) during model training and a higher Signal-to-Interference-plus-Noise Ratio (SINR) for the reconstructed signal, suggesting that the 2-D model requires less frequent temporal sampling. The study further investigates different sampling strategies and evaluates the influence of model order on signal reconstruction. Based on these assessments, a third-order 2-D AR is recommended as a suitable trade-off model for interference mitigation of FMCW radars for the evaluated scenarios. This paper is structured as follows: Section I defines the interference problem in FM CW radars and the latest solutions to this problem are discussed. Sections II and III include the working principles of FMCW radar and theoretical backgrounds about multi-dimension auto-regressive modeling, respectively. Eventually, the mitigation techniques and numerical evaluations of the proposed approach are presented in Sections IV and V. © 2024 Warsaw University of Technology.

This paper addresses the parameters that affect multiple interacting Frequency Modulated Continuous Wave radars, which can cause mutual interference. Multiple parallel chirp radars can shape ghost targets in the Range-Doppler plane as a unique case of mutual interference. In a real-world scenario, the carrier frequencies of the two radars are not synchronized. Therefore, the ghost will occupy a significant portion of the Range-Doppler plane, which can reduce the quality and clarity of the target signature and increase the false alarm in the detection process. By synchronizing two radars at the frame level, it has been tried to capture the ghost target's highest interfering condition and identify the radar circuit's influencing parameters on the chirp parallelization. This synchronizing FMCW radar system can minimize ghost targets and reduce mutual interference through a frequency-shifting algorithm that compresses the ghost targets. The result is an effective strategy for improving radar system precision and reliability in manageable environments with multiple interacting radar systems, which is crucial for future applications like autonomous vehicles and surveillance.