The Flatness Of The Array Signals And Wavelet Theory-based Road Detection System And Its Algorithm Research

In this paper, a multi-functions laser detection system for pavement roughness is introduced. An accurate pavement roughness information is acquired with theory of array signals processing and de-noising by wavelet in this system. In detail, the model of multi-sensors array signals processing, the theory of de-noising by wavelet, the method of road roughness detection and evaluation indexes, multi-function laser-detection system and its principle are introduced in this paper. Further more, the really application to pavement roughness detection based on array signals processing and wavelet theory is analyzed too. In this paper, a method to evaluate hardware performance of laser detection system with the array signal estimation is proposed. And the optimally weight vector of array signal can be acquired by the DOA estimating of received signals. In order to acquire the maximum output power of expected signals, summation of weight vector is applied. Based on the based on David L.Donoho soft-thresholding theory, the roughness information is re-constructed with multi-levels decomposition and de-noising of wavelet. Experiment results prove that this algorithm is a practical and effective method, with which the ideal cross-section curve can be acquired. The result is coincidence to the standard IRI (the International Roughness Index) and meets the necessity.