-
公开(公告)号：KR101687714B1
公开(公告)日：2016-12-19
申请号：KR1020150103262
申请日：2015-07-21
Applicant: 국방과학연구소
IPC: G01S13/524 , G01S5/06
Abstract: 본발명에따른위치탐지제어장치는, 다수의수신기, 상기다수의수신기로부터전파신호를수신하는트랜시버, 상기트랜시버에연결되어위치탐색을수행하는제어부를포함하되, 상기제어부는, 상기다수의수신기들의위치정보를수집하는단계, 타겟의방향, 상기타겟또는상기다수의수신기들의이동방향중 적어도하나에기반하여상기다수의수신기에수신되는가상신호에따른도래시간차(TDOA:Time Difference Of Arival) 및도래주파수차(FDOA: Frequency Difference Of Arival) 정보의인덱스를포함하는기준테이블을구성하는단계, 상기기준테이블로부터상기 TDOA 및 FDOA 정보를추출하는단계, 상기추출된 TDOA 정보에기반하여상기타겟의방향정보를추정하는단계, 상기추정된방향정보를이용하여기준도래각을선정하는단계를수행하여, 높은정확도를갖는정밀위치탐지방법을제공할수 있다.
-
公开(公告)号：KR101680155B1
公开(公告)日：2016-11-28
申请号：KR1020150020908
申请日：2015-02-11
Applicant: 국방과학연구소
Abstract: 본발명은마할라노비스거리기반펄스모호성해결을위한대상펄스선정방법에관한것이다. 본발명에따른마할라노비스거리기반펄스모호성해결을위한대상펄스선정방법은 LOB(Line Of Bearing) 간의교점을계산하는단계(S100); 상기계산하는단계(S100)에서계산된상기교점이이상치(Outlier)인지여부를각각판단하는단계(S200); 및상기판단하는단계(S200)에서이상치(Outlier)로판단된교점을제외한나머지교점을이용하여탐지영역을설정하는단계(S300);를포함한다. 본발명에따르면, 수신기사이의이격거리에비해작은 PRI값을가지는위협에대한레이더펄스모호성을해결하기위하여, 대상펄스영역을설정할때 다수의 LOB 교점에마할라노비스거리개념을도입하여교점들중 이상치를제거함으로써과대대상펄스설정영역문제를해결할수 있다.
Abstract translation: 本发明涉及一种用于解决基于马氏距离的脉冲模糊度的目标脉冲选择方法。 根据本发明，该方法包括：计算轴线（LOB）的交点的步骤（S100）; 确定在步骤（S100）中计算的交点是否为离群值的步骤（S200） 以及步骤（S300），通过使用除了在步骤（S200）中确定为异常值的交点之外的剩余交点来设置检测区域。 根据本发明，为了将雷达脉冲模糊度解决为威胁，具有比接收器之间的间隔距离更小的PRI值，该方法能够通过从交叉点移除异常值来解决过度的目标脉冲设置区域的问题 当设置目标脉冲区域时，通过将Mahalanobis距离的概念应用于多个LOB交点来实现。
-
公开(公告)号：KR101559904B1
公开(公告)日：2015-10-14
申请号：KR1020130156618
申请日：2013-12-16
Applicant: 국방과학연구소
IPC: G01S7/28
Abstract: 본발명은레이더신호 PRI 변조형태인식방법에관한것으로, 상기발명은표본코드를생성하는단계; 유전알고리즘수행을위해서해 집단(P[])을생성하는단계; 해집단의적합도를계산하는단계; 상기해 집단의적합도를기반으로해의쌍을선택하는단계; 상기해 집단의적합도기반으로선택된해의쌍을상기해 집단의적합도기반으로교배시키는단계; 상기해 집단의적합도기반으로선택된해에대한돌연변이를생성하는단계; 상기교배와상기돌연변이로변화된해 집단을새로운해 집단으로갱신하는단계; 세대종료조건을확인하는단계; 및최종 PRI 변조형태로판단하는단계를포함하는것을특징으로한다. 이에의해본 발명은누락펄스및 불요신호등의신호왜곡현상에강건하면서도자동화하기용이하다.
-
公开(公告)号：KR101449571B1
公开(公告)日：2014-10-13
申请号：KR1020140011401
申请日：2014-01-29
Applicant: 국방과학연구소
Abstract: The present invention relates to a method for estimating a location of a threat by resolving an ambiguity of selecting radar pulses and, more specifically, to a method for estimating a location of a threat by resolving an ambiguity of selecting radar pulses in a Time Difference Of Arrival (TDOA) system based on a genetic algorithm. The method of the present invention is configured to resolve the ambiguity of selecting the radar pulses for the threat having a small pulse repetition period value against a separation distance between electronic devices receiving the radar pulse and configured to be able to complement the weakness of a position estimation system using the TDOA with accuracy and fast convergence speed.
Abstract translation: 本发明涉及一种用于通过解决选择雷达脉冲的模糊度来估计威胁位置的方法，更具体地，涉及一种通过解析在时差中选择雷达脉冲的模糊度来估计威胁位置的方法 基于遗传算法的到达（TDOA）系统。 本发明的方法被配置为解决针对具有小脉冲重复周期值的威胁选择雷达脉冲与接收雷达脉冲的电子设备之间的间隔距离并被配置为能够补偿位置的弱点的模糊性 估计系统采用TDOA准确，收敛速度快。
-
公开(公告)号：KR101427149B1
公开(公告)日：2014-08-07
申请号：KR1020140026521
申请日：2014-03-06
Applicant: 국방과학연구소
IPC: G01S13/10
Abstract: The present invention relates to a radar signal recognition technique and, more specifically, to a method of recognizing a complex pulse repetition interval (PRI) modulation type through a support vector machine (SVM) by generating an exponential moving average signal using time of arrival (TOA) information of collected pulses and extracting a distinguishing factor after generating a signal by layer based on the exponential moving average signal.
Abstract translation: 雷达信号识别技术技术领域本发明涉及一种雷达信号识别技术，更具体地说，涉及一种利用支持向量机（SVM）通过使用到达时间产生指数移动平均信号来识别复数脉冲重复间隔（PRI）调制类型的方法 TOA）信息，并根据指数移动平均信号逐层生成一个区别因子。
-
Patent Agency Ranking
公开(公告)号：KR101394165B1
公开(公告)日：2014-05-27
申请号：KR1020140025507
申请日：2014-03-04
Applicant: 국방과학연구소
IPC: G06F3/03
CPC classification number: G06K9/6255 , G06F17/16 , G06K2209/01
Abstract: The present invention relates to a method for recognizing a user-adaptive cursive script in a smart device based on state transition probability. The method is realized in a manner of allowing a recognizer to train a cursive script inputted by a user, making a chain code, generated from the cursive script, into a state transition probability matrix, providing the recognizer with each of cursive script discriminating factors (P1-P9) extracted from the state transition probability matrix and then outputting the recognition result, terminating the recognition of the cursive script, when the recognition result is normal, and receiving a request for characters intended by the user and allowing the recognizer to retrain the characters, when the recognition result is abnormal. Thus, a writing style of a user can be recognized quickly with a high accuracy, a fast writing style (cursive script) with stronger user-specific font characteristics can be recognized as an exact writing style and, in particular, the poor performance and use of current smart devices can be extended by improving the character recognition of the smart devices.
Abstract translation: 本发明涉及一种基于状态转移概率来识别智能设备中的用户自适应草书的方法。 该方法以允许识别器训练由用户输入的草书脚本，使从草书脚本生成的链码变为状态转移概率矩阵的方式实现，向识别器提供草图脚本区分因素 P1-P9），然后输出识别结果，终止对草书脚本的识别，当识别结果正常时，接收对用户意图要求的字符的请求，并允许识别器重新训练 字符，当识别结果异常时。 因此，可以高精度地快速识别用户的书写风格，具有更强的用户特定字体特征的快速书写风格（草书脚本）可以被识别为精确的书写风格，特别是差的性能和使用 可以通过改进智能设备的字符识别来扩展当前的智能设备。
-
公开(公告)号：KR101300650B1
公开(公告)日：2013-08-27
申请号：KR1020130021671
申请日：2013-02-28
Applicant: 국방과학연구소
Abstract: PURPOSE: A method and a device for recognizing a pulse repetition interval (PRI) modulation form using a support vector machine (SVM) are provided to minimize an error rate in pattern recognition. CONSTITUTION: A receiving part (10) senses a radar signal to process and deliver to a control part (20). The control part is classified into an SVM training module (22), an input data characteristic vector extracting module (24), a classification result value check module by SVM (26), and a PRI modulation form discrimination module (28) in order to implement a PRI modulation form recognizing method. The SVM training module extracts a feature vector to input to an SVM from training data and includes the extracted feature vector and a PRI modulation form value. The SVM training module classifies the input data to input to SVM and trains the SVM by modulation forms using the input data. The classification result value check module by SVM puts the feature vector into the SVM by modulation forms implemented by the SVM training module. The PRI modulation form discrimination module selects a SVM with the greatest value among discrimination result values, produces a result code according to the selected SVM number, and recognizes the PRI modulation form using the result code. [Reference numerals] (10) Receiving unit; (20) Control unit; (22) SVM training module; (24) Input data characteristic vector extraction module; (26) SVM classification result check module; (28) PRI modulation type classifying module
Abstract translation: 目的：提供一种用于使用支持向量机（SVM）识别脉冲重复间隔（PRI）调制形式的方法和装置，以最小化模式识别中的错误率。 构成：接收部分（10）感测雷达信号以处理并传送到控制部分（20）。 控制部分分为SVM训练模块（22），输入数据特征向量提取模块（24），SVM（26）的分类结果值检查模块和PRI调制模式识别模块（28），以便 实现PRI调制形式识别方法。 SVM训练模块从训练数据中提取特征向量以输入到SVM，并包括提取的特征向量和PRI调制形式值。 SVM训练模块将输入数据分类为输入到SVM，并通过使用输入数据的调制形式训练SVM。 SVM的分类结果值检查模块通过SVM训练模块实现的调制形式将特征向量放入SVM中。 PRI调制形式识别模块在鉴别结果值中选择具有最大值的SVM，根据选择的SVM号码产生结果码，并使用结果码识别PRI调制形式。 （附图标记）（10）接收单元; （20）控制单元; （22）SVM训练模块; （24）输入数据特征向量提取模块; （26）SVM分类结果检查模块; （28）PRI调制型分类模块
-
8.发明授权TDOA/FDOA를 이용한 Gauss-Newton기법기반 신호원 위치추정방법 및 이를 이용한 신호원 위치추정장치 有权基于使用TDOA / FDOA的GAUSS-NETWON方法的局部化方法和使用该方法的本地化装置
公开(公告)号：KR101280513B1
公开(公告)日：2013-07-01
申请号：KR1020120129990
申请日：2012-11-16
Applicant: 국방과학연구소
IPC: G01S3/02
Abstract: PURPOSE: A signal source location estimating method and a signal source location estimating apparatus using the same are provided to simultaneously use time difference of arrival (TDOA) and frequency difference of arrival (FDOA), thereby improving the accuracy of location estimation. CONSTITUTION: A signal source location estimating method includes following steps. A location and speed vector estimation value about the location and speed vector of a radar signal source is set, and an initial value about transmission value is set (S110). A TDOA and FDOA estimation value is calculated using the location and speed vector estimation value and the transmission value set by the initial value (S120). A difference value between a TDOA and FDOA measurement value measured in a receiving part and the TDOA and FDOA estimation value is calculated (S130). A Jacobian matrix is generated by differentiating each of a TDOA model equation and an FDOA model equation which are prepared in advance using the TDOA and FDOA estimation value (S140). A weighted value for altering the location and speed vector estimation value is calculated using the difference value and the Jacobian matrix, and the location and speed vector estimation value is altered using the weighted value (S150). In case the difference value is higher than a permissible threshold value or the repeated number of control procedures in previous steps is lower than a maximum value, the control procedures in the previous steps are performed again (S160). If the difference value is lower than the permissible threshold value and the repeated number of the control procedures is higher than the maximum value, an altered location and speed vector estimation value is determined as a final location speed vector of the radar signal source (S170). [Reference numerals] (AA) Start; (BB) End; (S110) Set an initial value; (S120) Calculate a TDOA and FDOA estimation value; (S130) Calculate the difference value between a TDOA and FDOA measurement value and the TDOA and FDOA estimation value; (S140) Generate a Jacobian matrix; (S150) Alter the location and speed vector estimation value; (S160) Confirm whether the difference value is higher than a permissible threshold value; (S170) Determine the location and speed
Abstract translation: 目的：提供信号源位置估计方法和使用它的信号源位置估计装置，以同时使用到达时差（TDOA）和到达频差（FDOA），从而提高位置估计的精度。 构成：信号源位置估计方法包括以下步骤。 设置关于雷达信号源的位置和速度矢量的位置和速度矢量估计值，并设置关于传输值的初始值（S110）。 使用位置和速度矢量估计值和由初始值设定的传输值来计算TDOA和FDOA估计值（S120）。 计算在接收部分中测量的TDOA和FDOA测量值与TDOA和FDOA估计值之间的差值（S130）。 通过使用TDOA和FDOA估计值预先准备的TDOA模型方程和FDOA模型方程进行微分来生成雅可比矩阵（S140）。 使用差值和雅可比矩阵计算用于改变位置和速度矢量估计值的加权值，并且使用加权值来改变位置和速度矢量估计值（S150）。 在差值高于允许阈值的情况下，或者先前步骤中的重复控制程序数量低于最大值时，再次执行前述步骤中的控制步骤（S160）。 如果差值低于允许的阈值，并且控制过程的重复次数高于最大值，则将改变的位置和速度矢量估计值确定为雷达信号源的最终位置速度矢量（S170） 。 （附图标记）（AA）开始; （BB）结束; （S110）设定初始值; （S120）计算TDOA和FDOA估计值; （S130）计算TDOA和FDOA测量值与TDOA和FDOA估计值之间的差值; （S140）生成雅可比矩阵; （S150）改变位置和速度矢量估计值; （S160）确认差值是否高于容许阈值; （S170）确定位置和速度
-
公开(公告)号：KR101278541B1
公开(公告)日：2013-06-25
申请号：KR1020110109900
申请日：2011-10-26
Applicant: 국방과학연구소
Abstract: 본 발명은 다채널 디지털 수신 방법 및 장치에 관한 것으로, 다수 개의 안테나로부터 수신되는 N(N은 4 이상의 자연수)개 이상의 RF 신호를 A/D변환하여 디지털 신호로 변환하는 AD 변환기(ADC); AD 변환기로부터 N개 채널에서 디지털 신호를 입력받아 채널별 신호의 전력(power) 측정 후, 그 정보를 이용한 수신 신호의 세기가 가장 큰 채널(Max 채널)과 2번째, 3번째 채널(Max 채널의 좌, 우 채널)의 수신 채널을 선택하는 Power 측정 및 채널 선택부; Power 측정 및 채널 선택부에 의해 선택된 Max 채널의 신호에서 내부 또는 외부 고정밀 시각정보를 이용하여 수신신호의 세기가 가장 큰 신호에 대해 수 ns 해상도를 갖는 TOA를 측정하는 고해상도 TOA 측정부; Power 측정 및 채널 선택부에 의해 선택된 Max, 2nd, 3rd 채널에서 channelizer 필터를 사용하여 신호의 주파수, 신호 세기, 펄스폭을 측정하고, phase detector로 신호의 위상을 측정하는 채널라이저/위상 검출기; 채널라이저/위상 검출기로부터 제공된 각 채널별 동일한 주파수에 해당하는 신호의 위상과 세기를 동시에 이용하여 AOA를 측정하는 AOA 측정부; 및 고해상도 TOA 측정부, 채널라이저/위상 검출기, 및 AOA 측정부에서 각각 측정된 결과를 조합하여 펄스 단위로 PDW를 생성하는 PDW 생성부를 포함하고, 4개 이상의 수신 안테나 신호로부터 고해상도 TOA 측정이 가능하고, 동시에 펄스단위로 신호의 PDW 생성이 가능하다.
-
公开(公告)号：KR100761795B1
公开(公告)日：2007-09-28
申请号：KR1020060094474
申请日：2006-09-28
Applicant: 국방과학연구소
IPC: G01S13/06
Abstract: A method for recognizing PRI(Pulse Repetition Interval) modulation types of a radar signal by using a type classifier is provided to exactly recognize the PRI modulation type for a pulse train passing a pulse train separation process of a radar signal receiving and processing system under high-density multi-radar signal environment. A method for recognizing PRI(Pulse Repetition Interval) modulation types of a radar signal by using a type classifier comprises the steps of: aligning pulse arrival time information from pulse information of a received radar signal in order of time(10); generating a PRI sequence through first difference of the pulse arrival time(20); compensating an omitted pulse signal frequently generated under the real electromagnetic wave signal environment(30); calculating linear autocorrelation for a zero-center signal and normalizing the linear autocorrelation as a maximum value(40); extracting the first type classifier from the normalized linear autocorrelation(50); extracting the second type classifier from the normalized linear autocorrelation(60); compensating PRI modulation type distortion by the other emitter signal(70); computing the linear autocorrelation for a zero-center signal and normalizing the linear autocorrelation as a maximum value(80); extracting the third and fourth type classifiers from the normalized linear autocorrelation obtained through re-operation(90,100); and recognizing the PRI modulation type of the radar signal by comparing the type classifiers extracted in each step, with a pre-determined critical value for classifying the types.
Abstract translation: 提供了一种通过使用类型分类器来识别雷达信号的PRI（脉冲重复间隔）调制类型的方法，以精确地识别通过高频雷达信号接收和处理系统的脉冲串分离处理的脉冲串的PRI调制类型 密度多雷达信号环境。 通过使用类型分类器识别雷达信号的PRI（脉冲重复间隔）调制类型的方法包括以下步骤：根据接收到的雷达信号的脉冲信息按时间顺序对准脉冲到达时间信息（10）; 通过脉冲到达时间（20）的第一差异产生PRI序列; 补偿在实际电磁波信号环境（30）下频繁产生的省略的脉冲信号; 计算零中心信号的线性自相关并将线性自相关归一化为最大值（40）; 从归一化线性自相关（50）提取第一类分类器; 从归一化线性自相关（60）提取第二类型分类器; 通过另一个发射极信号（70）补偿PRI调制类型失真; 计算零中心信号的线性自相关并将线性自相关归一化为最大值（80）; 从通过重新获得的归一化线性自相关提取第三类和第四类分类器（90,100）; 并通过将每个步骤中提取的类型分类器与用于分类的预定临界值进行比较来识别雷达信号的PRI调制类型。
-
-
-
-
-
-
-
-
-
Search Results
41
records
(took 0.03 seconds)
