Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear progr...The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming （LP） based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming （OSIP） algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model （IMM） algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.展开更多
外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最...外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最小均方(Least Mean Square,LMS)对消算法。首先利用模糊函数估计杂波的频率和时延分布,构建含频率信息的多个参考信号。再把多个参考信号插入LMS算法中推导了扩展LMS算法,利用扩展LMS算法可以同时对消静、动杂波。扩展LMS算法能降低对消剩余,提高目标的信噪比,仿真分析和实测数据处理验证了算法的有效性。展开更多
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
基金supported by the National Natural Science Fundation of China (61203238 61134005+5 种基金 60921001 90916024 91116016)the National Basic Research Program of China (973 Program) (2012CB8212002012CB821201)the National Science Foundation for Postdoctoral Scientists of China (2012M520140)
文摘The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming （LP） based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming （OSIP） algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model （IMM） algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.
文摘外辐射源雷达利用直达天线接收的参考信号作为样本滤除目标回波中的杂波,但由于雨、云、树木或其他运动物体等的影响,回波内可能会包含非零频杂波,导致处理后杂波残余较大,影响目标检测。针对上述问题,提出了一种基于杂波识别的扩展最小均方(Least Mean Square,LMS)对消算法。首先利用模糊函数估计杂波的频率和时延分布,构建含频率信息的多个参考信号。再把多个参考信号插入LMS算法中推导了扩展LMS算法,利用扩展LMS算法可以同时对消静、动杂波。扩展LMS算法能降低对消剩余,提高目标的信噪比,仿真分析和实测数据处理验证了算法的有效性。
