Research of Velocity Detection Based on the Adaptive Weighted Average Algorithm

In recent years, the weighted average algorithm is discussed more and more. In order to maximize the Signal Noise Ratio (SNR) and minimize the variance of the signals, the weights are utilized. In this thesis, a traffic velocity detection of adaptive weighted-average is presented, in which, a reasonable result with enough precision could be got. Compared with other weighted average method, a large storage of data does not demanded in the adaptive weighted average algorithm. The simulation result is given too, which shows that the fitting curves of actual velocity and fused velocity is good enough to satisfy the actual demand of real-time completely.