Analytical Analysis of Poisson Point Process Distributed Automotive Radar Systems

In automotive radar applications, multiple radars are used in all vehicles for improving the imaging quality. However this causes radar-to-radar interference from neighbouring vehicles, thus reducing the imaging quality. One metric to measure the imaging quality is ranging success probability. The ranging success probability is the probability that a multiple radar system successfully detects an object at a given range, under certain operating conditions. In state-of-the-art literature, though distribution of fading in interferers is assumed to be arbitrary, closed form expression is derived only for no-fading assumption in both interferers and desired signal. As fading is always present in a wireless channel, we have derived ranging success probability assuming desired channel experiences the popular Rayleigh fading. We have also assumed generalized k-μ shadowed fading for interfering channels that generalizes many popular fading models such as Rayleigh, Rician, Nakagami-m, k-μ etc. The interferers are assumed to be located on points drawn from a Poisson point process distribution. We have also studied how the relationship between shadowing component and number of clusters can affect the impact of LOS component on ranging success probability.