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Modeling, Simulation and Analysis of Automotive Radar Signal Using Wavelet Transform Technique

An application of radar sensor in self-driven vehicles, to be used in detecting obstacles and providing accurate information about the vehicle’s ambient environment to activate appropriate control commands. There is need for the sensor to have a computing platform that can ensure real-time processing of the received signals. From previous works, appropriate algorithm, chip-set, memory, etc. capable of performing these tasks sufficiently, are the main challenges. This work model and simulate Radar Sensor signals; Radar signal for automated driving using Fast Fourier Transform (FFT) Technique. Analysis on the FFT Technique is carried out; in terms of its merits and demerits in this application. Applicability of Wavelet Transform (WT) technique for processing of Automotive Radar Signal (ARS) is demonstrated by offering WT Technique Solutions to FFT Problems for ARS by modeling and simulating the following: (a) 1-D Multi-signal WT Operations; (b) Solution to the Noise Problems – Wavelet Denoising; (c) Use of WT for Time-Frequency Reassignment and Mode Extraction with Synchrosqueezing; (d) Discrete Wavelet Transform (DWT) and Continuous Wavelet Transform (CWT) of an ARS with a Frequency Break. All simulations are done using the MATLAB R2017b software. The focused of this work is in the area of appropriate algorithm: to show how the WT technique and which of its tools, and how those tools could be used in developing appropriate algorithm for Automotive Radar Signal Processing (ARSP) as applied in self-driven vehicles.