Comparison of adaptive spectral estimation for vehicle speed measurement with radar sensors

Michail Antoniou, Mikhail Cherniakov, Edward Hoare, Liam Daniel, Khairul Khaizi Bin Mohd Shariff

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
224 Downloads (Pure)


Vehicle speed-over-ground (SoG) radar offers significant advantages over conventional speed measurement systems. Radar sensors enable contactless speed measurement, which is free from wheel slip. One of the key issues in SoG radar is the development of the Doppler shift estimation algorithm. In this paper, we compared two algorithms to estimate a mean Doppler frequency accurately. The first is the center-of-mass algorithm, which based on spectrum center-of-mass estimation with a bandwidth-limiting technique. The second is the cross-correlation algorithm, which is based on a cross-correlation technique by cross-correlating Doppler spectrum with a theoretical Gaussian curve. Analysis shows that both algorithms are computationally efficient and suitable for real-time SoG systems. Our extensive simulated and experimental results show both methods achieved low estimation error between 0.5% and 1.5% for flat road conditions. In terms of reliability, the cross-correlation method shows good performance under low Signal-to-Noise Ratio (SNR) while the center-of-mass method failed in this condition.
Original languageEnglish
Pages (from-to)751
Issue number4
Early online date2 Apr 2017
Publication statusE-pub ahead of print - 2 Apr 2017


  • speed estimation algorithm
  • speed over ground
  • Doppler radar sensor
  • vehicle speedometer


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