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Radar to detect the target , usually moving objects , such as aircraft , ships, etc. , but there is often a target around with a variety of clutter , such as ground clutter , clouds and rain clutter, sea clutter , enemy cast chaff clutter . The goal of this study is the strong sea clutter , weak target signal detection technology ; research in a weak signal-to-noise ratio and low probability of detection under the conditions of high maneuvering target tracking method in strong sea clutter conditions , the reliable detection of weak and highly maneuvering targets , stable track . Target detection algorithm using the grid method . By setting the coefficient of CFAR CFAR , CFAR processing results , and to meet the threshold of CFAR unit set the flag sent a follow-up to do the distance and orientation detection , and detect the start and end of the M / N standards . Target tracking algorithm to study the α-β algorithm Kalman filter algorithm and IMM Interactive multiple model algorithm , and compared three algorithms : α - β filter characteristics is not easy to select the decisions of α and β , Kalman filter can provide α-β filter do not have the filtering covariance matrix and maneuvering of the IMM algorithm can be assumed in a given time , the dynamic changes in the system can be used in the model of the M a precise representation . Matlab filtering results and the predicted results of the simulation target application three filtering algorithm , compared to three tracking algorithm α - β filter filtering point prediction point error is relatively large, the standard Kalman filter algorithm , coefficient optimization difficult , motor criteria is difficult to judge shortcomings , with a motor automatic judgments and integration of IMM multi- model algorithm , the algorithm is robust , less need to adjust the parameters , etc. , but also to achieve better tracking results .
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