The information extraction algorithm for a traffic detection radar using ISAR principle

Tao, Manyi; Li, Yong

doi:10.1109/apsar.2009.5374108

Cited by 1 publication

(1 citation statement)

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“…However, the conventional traffic surveillance radar systems suffer from both the high cost of its hardware and the corresponding large computation load due to the limitation of the individual measurement for a vehicle [2]. An interesting application of Frequency Modulated Continuous Wave (FMCW) radar systems for the traffic surveillance has been discussed in literatures [3]. The proposed FMCW radar system (see in Fig.1 (b)) has some properties that are distinctly different from the conventional one (see in Fig.1 (a)).…”

Section: Introductionmentioning

confidence: 99%

Improved Velocity Estimation Algorithm for Traffic Surveillance Radar Using Autofocus Technique

Xu¹,

Li²

2013

Proceedings of the 2013 International Conference on Remote Sensing,Environment and Transportation Engineering

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This paper is about an interesting application of the Frequency Modulated Continuous Wave (FMCW) radar system for the traffic surveillance. By introducing a novel monitoring mode, it is designed to provide synchronously the velocity measurements of all the vehicles within the radar footprint. To achieve a precise estimation of the real speeds of the moving vehicles, a Joint Maximum Contrast and Map Drift (JMCMD) algorithm using the autofocus technique is proposed in this paper. Those autofocus techniques originated from synthetic aperture radar data processing are analyzed and coupled here to form a two-step algorithm. Firstly, the maximum contrast method is used for a coarse estimation to get the rough velocity of the target. Then, the more accurate velocity of the target is obtained by using the map drift algorithm. The simulation results illustrate the errors of the measurement accuracy are less than 1km/h, which satisfy the practical requirements.

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Section: Introductionmentioning

confidence: 99%