A Graphical Heatmap Tool to Analyse the Effects of Interference in Automotive Radar

Norouzian, Fatemeh; Pirkani, Anum; Hoare, Edward; Cherniakov, M.; Gashinova, Marina

doi:10.1109/radarconf2043947.2020.9266353

Cited by 4 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All of the simulation and experimental analysis on the effect of various types of interference in different stages of FMCW radar signal processing shows that the effect of interference strongly depends on the victim and interference radar parameters. This illustrates the importance of a universal tool to identify the expected effects of interference [30].…”

Section: Interference Analysis In Various Domainmentioning

confidence: 99%

Phenomenology of automotive radar interference

Norouzian

Pirkani

Hoare

et al. 2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

Mutual interference in automotive radar is expected to become a major issue owing to the rapid increase in the number of vehicles on the road equipped with radar. The phenomenology of interference in frequency modulated continuous wave radar is presented. Interference is empirically analysed at every signal processing stage in the victim radar by means of experimentally verified simulation modelling. Knowledge of how interference manifests in different domains provides a useful tool to develop algorithms for interference detection, mitigation and/or avoidance. The receiver's filter response is analysed to minimise the interference duration and increase the effectiveness of time-domain mitigation techniques. A innovative method of interference parameter extraction by using spectrograms is also introduced.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Section: Interference Analysis In Various Domainmentioning

confidence: 99%

Phenomenology of automotive radar interference

Norouzian

Pirkani

Hoare

et al. 2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

show abstract

“…The chirp overlap plot of the transmitted chirp, received echo chirp, and received interference chirp are given in Figure 3a. The LPF with cut‐off frequency

f_{L P F}

limits the down‐converted interference to narrowband pulses with duration

Δ T_{int} = | 2 f_{L P F} / Δ k |

(Figure 3b) [24]. Figure 3c,d shows the zoomed regions from Figure 3b demonstrating down‐converted echo return and interference pulse, respectively.…”

Section: Fmcw Interference Modellingmentioning

confidence: 99%

“…A universal approach for interference power estimation as a function of

T_{s}

and

B W_{s}

is discussed in [24] and illustrated in Figure 10. Processing gain

(R_{S I R} (dB))

indicating signal to interference ratio (SIR) at the second FFT output, normalised to SIR at the receiver input is demonstrated.…”

Section: Statistical Analysis Of Interferencementioning

confidence: 99%

“…It can be observed that similar to Figure 7, the diagonal region shows a higher interference power and also a deviation from the statistics of AWGN. Moreover, for the cases corresponding to a close Gaussian approximation, but exhibiting higher interference power (due to a specific relation between interference and victim radar parameters [24]), the radar detection performance can still be adversely affected.…”

Section: Statistical Analysis Of Interferencementioning

confidence: 99%

See 1 more Smart Citation

Automotive interference statistics and their effect on radar detector

Pirkani

Norouzian

Hoare

et al. 2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

Millimetre‐wave frequency‐modulated continuous wave (FMCW) radars are at present widely deployed in the autonomous vehicles. The growing usage of such sensors, as a vital part of a robust future autonomous sensing system, sees the potential for significant increase in mutual interference and adverse effects on sensor operation. Effective target detection in the background of interference requires knowledge of the interference statistics. In the case that such statistics are found to be similar to that of additive white Gaussian noise (AWGN), then classical well‐established detection techniques can be applied. Conversely, if statistics are found to be different, traditional techniques (matched filtering) will not be optimal. Here, a statistical analysis of mutual interference within an FMCW victim radar is presented. The majority of cases show a low correlation between the interference pulses received at the victim radar, with close to a Gaussian distribution. Some specific cases show a high correlation between the interference pulses in the victim radar chirps with a sinusoidal‐like distribution, which degrades the victim radar’s detection performance. The presented analysis is validated by experimental data for various interference cases.

show abstract