Research On The Techniques Of Signal Detection In RTMS

Intelligent Transportation System is an important aspect of urban planning. Remote Traffic Microwave Sensor is a new radar vehicle detector, it has advantages of high precision, strong anti-interference, all-weather, easy to install, small size, easy-to-mobile and so on. Therefore, Intelligent Transportation Systems use this technology in the vehicle detection and monitoring.This thesis introduces the research of signal detection in RTMS system. First, it shows the working system, the basic working principle and performance of RTMS. Second, it researches simulation of the vehicle target echo, noise and clutter. We give a quantitative analysis of linear frequency modulated continuous wave and the detail echo signal model in RTMS system. Focusing on the signal processing techniques of RTMS system, it uses the wavelet thresholding method for signal denoising, and the probability density statistics of lane position to identify the lane range. The threshold setting method for divided traffic lane is presented, which based on the constant false alarm rate and automatic lane identification. The CFAR threshold is set in the divided lane, and set the second threshold to judge the result. We put forward speed and the vehicle inspection program. Verify the correctness of the echo signal as well as the feasibility of signal processing methods through the simulations in MATLAB.At last, it introduces the DSP software architecture of this system, and gives the detection algorithm program. Compared with the simulation results in MATLAB, it achieves the system requirements.