Wave Automotive Radar Research Articles

The signal processing algorithm of automotive FMCW radars with an extended range of speed estimation

The paper considers the algorithm for estimating the speed and distance to the target as applied to the mm wave automotive radar with linear FMCW. To extend the range of target speed estimation, a signal in the form of a Chirp Sequence Waveform is used with a shift of the initial frequency in the adjacent chirps of the frame. A mathematical model of the received microwave signal is proposed, taking into account a wide range of velocity changes of the target, as well as the effect of additive white Gaussian noise on the radar receiver. It is shown that the signal-to-noise ratio of 10 dB is necessary for the algorithm to work, and that the unambiguity and consistency of the speed estimate is limited by the first two Nyquist zones for the Doppler frequency.

Test bench development for signal registration in millimeter wave automotive radars

A development of a bench for automotive radar signals registration and analysis is considered in this paper. The bench is based on the AWR1642boost evaluation module with 77 GHz carrying frequency. Supporting software is developed to help signal analysis and reflection model creation. The bench aims an investigation of signal reflection properties from some specific types of obstacles and the development of the reflection mathematical models.

Automotive Radar Interference Mitigation Using Adaptive Noise Canceller

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio. In a quadrature receiver, the interference in the positive half of frequency spectrum is correlated to that in the negative half of frequency spectrum, whereas the beat frequencies from real targets are always present in the positive frequency. Thus, we estimated the power of the negative frequency as an indication of interference, and fed the positive frequency and negative frequency components into the primary and reference channel of an adaptive noise canceller, respectively. The least mean square algorithm was used to solve for the optimum filter solution. As a result, both the simulation and experiment showed a good interference mitigation performance.