Research On Methods Of Target Data Correlation Under Strong Clutter Interference

When the radar radiates electromagnetic waves to space to detect airborne targets, the receiver has received radar signals except the reflective echo signals of airborne targets from the detected direction within the sight, there may be existing a large number of backscattered strong interference clutter signals which are from ground,sea,aerial objects such as clouds, rain and so on.The existence of these strong interference clutter is not only covered or submerged the echo signals of aerial useful targets, but also the strong clutter’s jamming signal of the land, sea and weather will lead to radar generating large number of false target signal.And the existence of numerous false target signal, it not only affects the associated accuracy and the tracking precision of targets in the radar data processing, but also tends to cause invalid of target detection and tracking in radar system.Therefore, in order to adapt to the modern complex battlefield environments, in the radar data processing, to further study and explore the new algorithms or new methods of radar data processing,to filter out the useless clutter ingredient in the radar received echo, and to extract useful target information remains current focus of attention and research of many scholars at home and abroad.This article is mainly aiming at the research of radar multi-target data associated methods under the intensive strong clutter environment, the involving contents mainly include the following aspects:(1) The radar data processing method in the intensive strong clutter environment is the emphasis of modern radar research.Therefore, this article conductes the comparison and analysis of the traditional common target data associated methods of radar, and gives its deficiencies.(2) Aiming at clutter data having the characteristics of small samples and poor information, a clutter filtering algorithm based on gray correlated analysis is presented.Namely,using grey correlated analysis of grey system theory, and improved GM (1,1) analyzable model to establish the gray filter wave gate model, so as to improve the effect of filtering clutter under the intensive environment.Through the simulated comparison of commonly used rectangular filtering wave gate and the grey filter wave gate which is established by the method of this paper, it can conclude that the established method of this paper is better than the traditional rectangular filtering wave gate.(3) For most of the traditional radar multi-target tracking data associating method,it exists problems of low correlation accuracy,high algorithm time-consumption and so on.An improved algorithm based on the multiple hypothesis and target tracking correlation algorithm is put forward. Through the analysis of the shortcomings such as large amount of calculation, the lack of effective hypothesis management which is existed in traditional multiple hypothesis and target tracking associated algorithms. This paper adopts the methods of grouping, classification and establishing the optimization hypothesis management mechanism for radar data, and to reduce the amount of calculation and improve the accuracy of correlation.With traditional JPDA algorithm, classic m-optimal MHT algorithm, and the algorithms in documents [60], comparing the simulation and analysis results show that the algorithm not only associated with high precision in this paper, and the algorithm of time, it is convenient to be used in engineering practice.