AUTOMOTIVE RADAR INTERFERENCE MITIGATION VIA SINR MAXIMIZATION

The mutual interference mitigation between identical or similar radar systems in autonomous driving has gained wide spread attention from both academia and industry. The resulted ghost target interference will reduce the sensitivity of the radar sensor and increase the false alarm rate. To tackle this problem, in this paper, we make full use of two characteristics of interference to achieve ghost target interference mitigation in the Doppler domain. The key insight lies in the fact that the interference is one-way propagation, and thus the resulted ghost target can be converted to the noise floor in the Doppler domain through random slow-time coding. Moreover, the high power characteristic of interference allows us to further enhance the interference mitigation performance by adopting a signal-to-interference-plus-noise ratio (SINR) maximization principle. Numerical examples are provided to demonstrate the effectiveness of the proposed interference mitigation approach.