77 GHz ACC radar simulation platform

Kärnfelt, Camilla; Peden, Alain; Bazzi, Ali M.; Shhade, Ghayath El Haj; Abbas, Mohamad; Chonavel, Thierry

doi:10.1109/itst.2009.5399354

Cited by 34 publications

(21 citation statements)

References 5 publications

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“…The chirp sequence is designed so as to meet the maximum detectable relative velocity v max = 140 km/h, the maximum detectable range d max = 150 m when B c = 0 (since it increases for RadCom), velocity resolution smaller than 1 m/s and range resolution of 15 cm. Radar front-end-hardware component parameters are taken as in [17]. The mean value for the radar cross section of a car is taken as 20 dBsm [17], [20].…”

Section: A Simulation Parametersmentioning

confidence: 99%

Radar Communications for Combating Mutual Interference of FMCW Radars

Aydoğdu

Garcia

Hammarstrand

et al. 2019

2019 IEEE Radar Conference (RadarConf)

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Commercial automotive radars used today are based on frequency modulated continuous wave signals due to the simple and robust detection method and good accuracy. However, the increase in both the number of radars deployed per vehicle and the number of such vehicles leads to mutual interference, cutting short future plans for autonomous driving and active safety functionality. We propose and analyze a radar communication (RadCom) approach to reduce this mutual interference while simultaneously offering communication functionality. We achieve this by frequency division multiplexing radar and communication, where communication is built on a decentralized carrier sense multiple access protocol and is used to adjust the timing of radar transmissions. Our simulation results indicate that radar interference can be significantly reduced, at no cost in radar accuracy.

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Section: A Simulation Parametersmentioning

confidence: 99%

Radar Communications for Combating Mutual Interference of FMCW Radars

Aydoğdu

Garcia

Hammarstrand

et al. 2019

2019 IEEE Radar Conference (RadarConf)

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“…for target radar cross section 2 (RCS) σ, transmitter and receiver antenna gains G tx and G rx , w(t) is additive white Gaussian noise (AWGN) with power spectral density N 0 , c denotes the speed of light and λ r is the wavelength of the radar carrier. The received signal is processed by the following blocks [42]: a mixer, an ADC, and a digital processor ( Fig. 1).…”

Section: Radcom Receivermentioning

confidence: 99%

RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation

Aydoğdu

Keskin

Garcia

et al. 2021

IEEE Trans. Intell. Transport. Syst.

110

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In the automotive sector, both radars and wireless communication are susceptible to interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate interference in both systems. This article analyses the mutual interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of interference among FMCW based automotive radars, including self-interference, using radar communications. The results show that RadChat can significantly reduce radar mutual interference in single-hop vehicular networks in less than 80 ms.

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“…Mathematically stopping time obtained by following equation: τstop = vego/abrake (1) When FCW system will alert drivers for imminent collision with a lead vehicle, it is expected to react to the alert and apply the brake with a delay time τreact . Total time taken by ego vehicle to travel before colliding with lead vehicle is given by:…”

Section: Simulationmentioning

confidence: 99%

Implementation of European NCAP Standard Autonomous Emergency Braking Scenarios Using Two Leddar M16 Sensors

Kapse

Adarsh

2019

Advances in Intelligent Systems and Computing

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In this paper we have implemented the autonomous emergency braking using two radar sensors with different angle of coverage. The synthetic radar data is generated by radar detection generator block available in AEBTestBench simulation module. AEBTestBench is autonomous emergency simulation module available in Matlab 2018b version under ADAS toolbox. From different EURO NCAP standard scenarios available, we have covered 5 scenarios with their results analysis showing where forward collision warning is displayed and what is the AEB status. The observation of simulation results are carried out for 10 seconds. Data fusion for two radar sensors is carried by Kalman filter algorithm present inside the simulation module.

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77 GHz ACC radar simulation platform

Cited by 34 publications

References 5 publications

Radar Communications for Combating Mutual Interference of FMCW Radars

Radar Communications for Combating Mutual Interference of FMCW Radars

RadChat: Spectrum Sharing for Automotive Radar Interference Mitigation

Implementation of European NCAP Standard Autonomous Emergency Braking Scenarios Using Two Leddar M16 Sensors

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