Research And Implementation Of Target Detection Algorithm Based On Clutter Map

Radar needs to detect the target under the influence of clutter,noise and interference with undulating characteristics.Constant false alarm rate(CFAR)processing is the core of radar target detection technology.The clutter map constant false alarm rate(CM-CFAR)processing is suitable for the environment where the clutter spatial intensity varies dramatically,and it is an important research direction of radar CFAR processing.In addition,as an important part of zero Doppler processing,CM-CFAR plays an irreplaceable role in low-speed target detection.The CM-CFAR processing and its application in low-speed target detection are focused on in this thesis.In a pulse compression radar signal processing system,a method based on clutter map is given to complete the detection of low-speed target in combination with Kalmus filter and the improved CM-CFAR using maximum cell.It has better performance of low-speed target detection in clutter edge environment.In this thesis,the basic theory of radar CFAR processing is studied firstly,the characteristics of conventional radar clutter,the Neyman-Pearson criterion and its reasons as a general radar detection criterion are analyzed,and the single pulse optimal detection under the condition of constant Gaussian white noise is studied.For the CFAR algorithm,three ML-CFAR algorithms are studied,such as CA-CFAR,GO-CFAR and SO-CFAR.The detection instance and applicable conditions of each algorithm are simulated and analyzed.The influence of the number of reference cells on the detection performance of ML-CFAR is analyzed in detail,then three ML-CFAR algorithms are compared.For the clutter environment which changes slowly with time and dramatically in space,the CM-CFAR processing is focused on in this thesis.The basic principles of clutter maps is studied,including the establishment methods,clutter map classification and the role of various clutter maps and so on.Then the Nitzberg CM-CFAR,CACM-CFAR,hybrid CM/LCFAR,and CM-CFAR using maximum cell are focused on.The detection instance of each algorithm is simulated and the application of the algorithm is illustrated.The effects of forgetting factor,iteration number,threshold factor and number of reference cells on the detection performance of CM-CFAR are analyzed in-depth,and the value of the optimal forgetting factor of these CM-CFAR algorithms is discussed.For the low-speed target detection,the zero-speed filter and the CM-CFAR algorithm in zero Doppler processing are studied,and the reason for using zero Doppler processing is analyzed.The Kalmus filter is studied emphatically,and CM-CFAR using maximum cell is improved to make it better for low-speed target detection in clutter edge environment.Then based on the Kalmus filter and the improved CM-CFAR using maximum cell,a method of low-speed target detection based on clutter map is given to achieve low-speed target detection under strong ground clutter background.In the implementation of the method,the system implementation scheme is given in combination with a pulse compression system radar signal processing system.Combined with the cancellation branch and zero Doppler processing,the overall design of the target detection algorithm is carried out,and the method is implemented on TS201 DSP.The data collection was carried out near the airport,then the measured data was processed and the test results were analyzed,which proved the effectiveness of the algorithm described in this thesis.