Mutual Interference Mitigation for Multiple Connected Automotive Radar Systems

Abstract

The number of commercial and civilian vehicles equipped with automotive radars is expected to rise rapidly in the forthcoming years and with that comes the problem of increased mutual interference between the radar sensors, which can result in severely reduced radar sensitivity and increased false alarm rates. The difficulty and complexity of the problem increase with MIMO radar systems and multiply even further with a growing number of vehicles present on the scene. A system of connected vehicles can efficiently address this problem by sharing information amongst themselves. In this paper, we propose an efficient waveform design algorithm that seeks to minimize a collective cross-ambiguity function. Vehicles that can talk to each other, can perform the design online in a collaborative manner, or offline, in which case the radar codes can be designed and stored in a codebook for future use. The proposed coding scheme is computationally efficient for practical use and the incorporation of such schemes requires only a slight modification of the existing systems. Our numerical examples indicate that the proposed scheme can significantly reduce the interference power level in a desired area of the radar cross-ambiguity functions.

Random Time Division Multiplexing Based MIMO Radar Processing with Tensor Completion Approach

“…Finally, the detected complex scattering signals of the target in the range-Doppler domain of each channel form the receiving vector, from which the target angle information can be obtained by using the spectral analysis method [ 7 ]. Although the above processing flow is relatively complete and fixed, it still faces many challenges [ 8 ], including how to improve the orthogonality between transmit channels via waveform coding [ 9 , 10 , 11 , 12 , 13 ], which can greatly reduce the mutual interference [ 14 ]. In addition, there are other problems worth investigating, e.g., target sidelobe suppression [ 15 ] or multi-channel amplitude and phase error calibration [ 16 ].…”

Fast Joint DOA, Range, and Velocity Estimation Method for FMCW MIMO Radar via PARAFAC

“…O VER the recent years, multiple-input multiple-output (MIMO) radar technology has been widely adopted with the booming development of autonomous driving technology [1]- [4], which can enhance the resolution of directionof-arrival (DOA) estimation by matching the transmitting and receiving arrays to construct a large virtual aperture [5]- [7]. Moreover, frequency-modulated continuous wave (FMCW) radar has good range measurement capability as well as low power consumption [8].…”

Code Optimization and Angle-Doppler Imaging for ST-CDM LFMCW MIMO Radar Systems

“…Multiple-input multiple-output (MIMO) radar can achieve high angular resolution with a relatively small number of antennas [3][4][5][6], and MIMO radar has become a standard for automotive applications. Because of the low cost advantage, most of the existing automotive radar systems are linear frequencymodulated continuous-wave (LFMCW) MIMO radar systems [7][8][9].…”