Speed Estimation in Forward Scattering Radar Using Standard Deviation and Improved Zero-Crossing Method

Current research on Forward Scattering Radar (FSR) dedicates to the target detection and classification. In the classification technique, the target’s speed information is required prior to the classification processes. Unfortunately, the speed is hidden inside the received signal and cannot be extracted directly. This is due to the loss in range resolution in FSR system. This is the main disadvantage of FSR. Thus, this thesis presents a work on speed estimation in FSR. Theory of FSR systems is briefly described together with practical experiments to evaluate the feasibility of such a system in real-life scenarios. The data collected from the practical experimentation and typical ground vehicle is used as the target (e.g. car, lorry). The overall speed estimation system is described. For vehicle speed estimation, two methods are proposed: the first method applies Standard Deviation (STD) theory to the raw radar signal. In the second method, the number of zero-crossing in the received signal is analyzed for speed estimation. On top of that, de-noising pre-processing is introduced to increase the accuracy of speed result. These two methods show a good result in estimating the vehicle speed crossing FSR baseline.From the analysis, speeds estimation using STD work best for high SNR value. By analyzing 917 experimentally obtained car signatures, the performance of the system is evaluated and the effectiveness of the system is confirmed.

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