A simulator for multi-user automotive radar scenarios

Schipper, Tom; Schlichenmaier, Johannes; Ahbe, Dora; Mahler, Tobias; Kowalewski, Jerzy; Zwick, Thomas

doi:10.1109/icmim.2015.7117928

Cited by 5 publications

(3 citation statements)

References 6 publications

(8 reference statements)

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“…Further analytic attempts to investigate automotive radar interference can be found in [12] which studies the desiredto-undesired signal power ratio in ultra wideband automotive radar, also in [13] and [14] utilizing Frequency Modulation Continuous Wave (FMCW) as a modulation scheme. Simulation approaches can be found in [15] and [16], mainly based on ray tracing with scenario specific simulation environments. To summarize, our understanding of the available literature on automotive radar interference, we list the following points:…”

Section: Background and Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic Geometry Methods for Modeling Automotive Radar Interference

Al‐Hourani

Evans

Kandeepan

et al. 2018

IEEE Trans. Intell. Transport. Syst.

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As the use of automotive radar increases, performance limitations associated with radar-to-radar interference will become more significant. In this paper we employ tools from stochastic geometry to characterize the statistics of radar interference. Specifically, using two different models for vehicle spacial distributions, namely, a Poisson point process and a Bernoulli lattice process, we calculate for each case the interference statistics and obtain analytical expressions for the probability of successful range estimation. Our study shows that the regularity of the geometrical model appears to have limited effect on the interference statistics, and so it is possible to obtain tractable tight bounds for worst case performance. A technique is proposed for designing the duty cycle for random spectrum access which optimizes the total performance. This analytical framework is verified using Monte-Carlo simulations.

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Section: Background and Related Workmentioning

confidence: 99%

“…This integration is performed over the region of interest R, where in our case it represents the active interferers region R ∈ [δ o , ∞]. Thus, using (17) we can continue to simplify (16) where we drop the x notation in g x since it is an i.i.d random variable:…”

Section: B Interference Distributionmentioning

confidence: 99%

Stochastic Geometry Methods for Modeling Automotive Radar Interference

Al‐Hourani

Evans

Kandeepan

et al. 2018

IEEE Trans. Intell. Transport. Syst.

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show abstract

“…The variety of interference levels grows even further when the experiment includes multiple interferers. Effects of multiple interfering radars on the performance of automotive radars have been covered in [5][6][7][8][9]. These publications focus on the influence of spatial arrangements of the scenario on the radio channel.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Interference Between Vast Numbers of Automotive Radars Considering Stochastic Temporal Conditions

Hahmann¹,

Schneider²,

Zwick³

2020

PIER M

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With a constantly increasing number of cars equipped with 77 GHz automotive radar, the performance degrading effects of crosstalk are becoming a rising threat to radar-enabled automated driving functions. Since interference is sensitive to slight changes of temporal and spatial conditions of the scenario, meaningful measurements are hard to conduct which is why simulations are an important supplement. In this paper, a simulation model is introduced that estimates the distribution of the reduction of the detection range of automotive radars due to multiple interferers focusing on stochastic temporal conditions. The underlying system model calculates the direction-and timing-dependent influence of one single interferer on the detection range of the host radar. The model is kept simple, making it suitable for Monte Carlo methods, which allow the indispensable statistical evaluation of the broadly spread results. Finally, a method is presented that transfers multiple statistics regarding single interferers into a single environment. The computing time of the simulation grows linearly with the number of interfering radars, so the effects of vast numbers of interferers can be studied using this simulation model. Statistical evaluations of the detection performance degradation of a front-mounted radar in sample highway scenarios, containing up to ten interfering radar sensors, are performed in this paper.

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