Abstract
Radar signals generated from other vehicles can act as interference to ego-vehicle, which degrades the inherent detection performance of radar. In this paper, we address an efficient solution to the interference problem in frequency-modulated continuous wave (FMCW)-based automotive radar systems, named geometric sequence decomposition based interference cancellation (GSD-IC). With the method of GSD-IC, we can decompose the received signal into different non-orthogonal superposed signals, which means the interference signal and the signal reflected from the desired target are separated. It is based on the facts that 1) each single sampled signal can be interpreted as a geometric sequence and 2) the useful physical features, such as the time delay and the Doppler frequency, are extracted after converting the superposition of these geometric sequences into several transformed matrices. Through this approach, we can achieve effective interference signal cancellation while minimizing the loss of meaningful target information. Moreover, the proposed method does not require the generation of specific radar waveforms, and can mitigate interference through signal processing even with existing waveforms. Numerical results show that our algorithm outperforms existing methods in various scenarios.
Highlights
In recent years, automotive sensors for autonomous driving, such as radar, lidar, camera, and ultrasonic sensors, are getting attention
When an frequency-modulated continuous wave (FMCW) radar signal transmitted from another vehicle is received by the radar of ego-vehicle, the signal acts as an interference
We explore the potential of the geometric sequential representation in time and frequency domains to pinpoint the desired and interference signals in the FMCW radar systems
Summary
Automotive sensors for autonomous driving, such as radar, lidar, camera, and ultrasonic sensors, are getting attention. The radar signals received by the ego-vehicle includes signals reflected from the desired target and the interferer, and even a signal transmitted from the interferer Those signals have different characteristics in the complex gain, time delay, and the Doppler shift. We exploit the fact that the non-orthogonally overlapped K baseband signals, i.e., the mixture of desired and interference signals, constitute a superposition of K geometric sequences This mathematical property converts the joint delay and Doppler estimation problem in the FMCW radar systems into the extraction of the parameters of geometric sequences from the two-dimensional (2D) data samples. The most notable property of geometric sequence decomposition based interference cancellation (GSD-IC) is that it results in the high resolution for joint delay and Doppler estimation This is because the proposed scheme directly extracts the intrinsic information of the received signal.
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