The purpose of the paper is as following : ( 1 ) the study of data fusion between ais target and radar target can partly resolve the problem of leak and fault track and the problem of target exchange 本文的研究的意义有以下三个方面： ( 1 )研究ais目标与雷达目标的数据融合可以部分的解决雷达目标跟踪的错漏跟踪和目标交换问题。
When the radar is narrow band , radar target is studies as a point target . target and clutter are modeled as having a zero - mean complex gaussian probability density function ( pdf ) . target is assumed as slowly - fluctuant 窄带条件下,雷达目标可以看作是一个点目标,假设目标和杂波都服从零均值的复高斯分布,目标为慢起伏。
Abstract : a radar target detector unit based on multi - dsp combined with fpga was presented , the software flow chart for system work is given and the demand speed for real - time process was estimated 文摘:介绍了以多片dsp和可编程器件可编程门阵列( fpga )相结合构成的雷达检测录取单元，给出了系统的软件流程图，分析了实时处理的速度。
So this technical may improve the detecting performance . the relation between radar target _ detecting based on the radar ppi and radar t _ r system , singnal processor system is very little which is good to modify the old radar 另外，基于ppi的雷达目标检测与雷达收发系统、信号处理系统的直接关系不大，这对于老式非相参雷达的数字化改造十分有利。
In this paper , to probe into key problems of feature extraction , a systematic study is performed not only about understanding and processing radar target image , but also parametric modeling of 2 - d target scattering centers and parameter estimation 围绕这一课题，本文研究了雷达目标二维像的理解与处理，及二维散射中心的建模与参数估计问题。
Radar target recognition ( rtr ) is very valuable for military application . the performance of rtr can be improved greatly by identity fusion . this dissertation deals with the rtr using data level and decision level fusion 雷达目标识别具有巨大的军事应用价值，通过身份融合技术能提高雷达目标识别的性能，本文主要研究数据层和决策层融合雷达目标识别。
Under the high - resolution imaging radar background , extracting electromagnetic scattering features of target from 2 - d radar data , is a task valuable for both theoretical research and practical usage in field of radar target recognition 在高分辨成像雷达体制下，基于雷达目标二维像的散射特征提取，是雷达目标识别领域中一项理论意义与实用价值兼备的课题。
It can cancel the harmonic phenomena along cross directions and deduce the cost of computation . in chapter four using the impulse characteristics of inciding wave , we test the energy peaks in the transient impulse response of radar targets 本文第四章用能量峰概念和微分参数估计的方法，在时域研究了目标脉冲响应的特性，该方法可以分解出目标上不同散射中心的散射波。
The radar targets identification based on svm is studied in chapter 5 . with the balance of the empirical risk minimum and complication , the method has a better classification performance . the validity of these methods are verified by experiments on simulated data 支持向量机方法在理论上摆脱了bp网络的缺陷,同时实现了经验风险和推广能力的折衷,实验结果证明了该方法的有效性。
Two popular statistical - based techniques , namely , bayes and dempster - shafer methods are applied to develop radar target identification algorithms for our application . the performance of bayes method and d - s method is compared in convergence time and robustness 运用两种普遍使刚的统计推断方法? bayes方法和d - s证据理论对以上空中目标进行识别，比较了它们的收敛时间和稳健性。
