CN107038340B - The device and method of thermal noise data is found in a kind of A/C and S mode overlap signal - Google Patents

The device and method of thermal noise data is found in a kind of A/C and S mode overlap signal Download PDF

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CN107038340B
CN107038340B CN201710221052.5A CN201710221052A CN107038340B CN 107038340 B CN107038340 B CN 107038340B CN 201710221052 A CN201710221052 A CN 201710221052A CN 107038340 B CN107038340 B CN 107038340B
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刘卫东
彭卫
郭建华
张凯
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Second Research Institute of CAAC
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Abstract

本发明公开一种A/C模式和S模式交叠信号中寻找热噪声数据的装置及方法。该装置包括数据采集单元、数据处理单元和数据输出单元;数据采集单元用于采集A/C模式和S模式交叠信号中一段信号数据;数据处理单元用于将采集的信号数据进行处理,并发送到所述数据输出单元;数据输出单元用于将数据处理单元处理后的数据输出;本发明提出的装置和方法,可在任意长的A/C模式数据和噪声、S模式信号数据和噪声或A/C模式数据+S模式信号数据和噪声所构成的交叠数据段中寻找出热噪声数据,该方法具有较好的实时性和自适应性,可以较好地实现交叠数据中热噪声数据数据及其统计特性的估计。实际中该方法可以不限于热噪声数据的寻找,还可发现杂波或具有随机性质数据的寻找。

The invention discloses a device and method for searching thermal noise data in overlapping signals of A/C mode and S mode. The device includes a data acquisition unit, a data processing unit and a data output unit; the data acquisition unit is used to collect a section of signal data in A/C mode and S mode overlapping signals; the data processing unit is used to process the collected signal data, and Sent to the data output unit; the data output unit is used to output the data processed by the data processing unit; the device and method proposed by the present invention can be used in arbitrary length A/C mode data and noise, S mode signal data and noise or A/C mode data + S mode signal data and noise to find thermal noise data in the overlapping data segment, this method has good real-time and adaptability, and can better realize the thermal Estimation of noisy data data and their statistical properties. In practice, this method is not limited to the search for thermal noise data, but also for finding clutter or data with random properties.

Description

一种A/C和S模式交叠信号中寻找热噪声数据的装置及方法A device and method for finding thermal noise data in A/C and S mode overlapping signals

技术领域technical field

本发明涉及热噪声数据处理领域,特别涉及一种A/C和S模式交叠信号中寻找热噪声数据的装置及方法。The invention relates to the field of thermal noise data processing, in particular to a device and method for searching thermal noise data in A/C and S mode overlapping signals.

背景技术Background technique

A/C模式和S模式是MLAT(多点监视技术)系统、ADS-B(广播式自动相关监视)和二次雷达系统的主要通信链路协议,已广泛应用于民航交通管制领域。A/C模式和S模式信号的中心频率均为1090MHz,且都属于脉位调制,即利用子脉冲的位置和电平来表示信息。A/C mode and S mode are the main communication link protocols of MLAT (Multipoint Surveillance Technology) system, ADS-B (Automatic Dependent Surveillance-Broadcast) and secondary radar system, and have been widely used in the field of civil aviation traffic control. The center frequencies of the A/C mode and S mode signals are both 1090MHz, and both belong to pulse position modulation, that is, the position and level of the sub-pulse are used to represent information.

在实际中,往往需要精确地对A/C模式和S模式接收信号中热噪声的统计特性进行估计,所估计出热噪声的统计特性将在后续的解码过程中起到关键作用。In practice, it is often necessary to accurately estimate the statistical properties of the thermal noise in the A/C mode and S mode received signals, and the estimated statistical properties of the thermal noise will play a key role in the subsequent decoding process.

常规热噪声的统计特性估计方法是找到一段无信号(A/C模式和S模式信号)的数据段(即数据中只存在热噪声)来进行估计。在实际中,该方法存在如下两个问题:The statistical characteristic estimation method of conventional thermal noise is to find a data segment with no signal (A/C mode and S mode signal) (that is, only thermal noise exists in the data) for estimation. In practice, this method has the following two problems:

⑴当发射源数目较多时,实际数据中往往存在着如下情况:不同幅度、不同长度A/C模式和S模式信号进行交叠,表现为在较长的接收数据段中都存在着信号+噪声,难以找到一段足够合适的数据段(只存在热噪声的数据)来进行热噪声统计特性的估计。(1) When the number of transmitting sources is large, the following situation often exists in the actual data: A/C mode and S mode signals of different amplitudes and lengths overlap, showing that there are signals + noise in the longer received data segment , it is difficult to find a suitable enough data segment (data with only thermal noise) to estimate the statistical characteristics of thermal noise.

⑵实际中,系统及环境性质都在发生变化,需要实时和自适应地对热噪声特性进行估计,常规方法的实时性和自适应性较差。(2) In practice, the properties of the system and the environment are changing, and it is necessary to estimate the thermal noise characteristics in real time and adaptively, and the real-time and adaptive properties of conventional methods are poor.

本发明提出了一种方法,可在任意长的A/C模式数据+噪声、S模式信号数据+噪声或A/C模式数据+S模式信号数据+噪声所构成的混合数据段中寻找出热噪声数据,该方法具有较好的实时性和自适应性,可以较好地实现热噪声统计特性的估计。The present invention proposes a method, which can find heat generation in a mixed data segment composed of A/C mode data+noise, S mode signal data+noise or A/C mode data+S mode signal data+noise. Noise data, this method has better real-time and adaptability, and can better realize the estimation of statistical characteristics of thermal noise.

实际中该方法可以不限于热噪声数据的寻找,还可发现杂波或具有随机性质数据的寻找。In practice, this method is not limited to the search for thermal noise data, but also for finding clutter or data with random properties.

发明内容Contents of the invention

本发明的目的是提供一种A/C和S模式交叠信号中寻找热噪声数据的装置及方法,在时间域上,设置一个数据滑动窗口,该数据滑动窗口不断在所接收信号的数据序列上进行滑动,判断和寻找出满足统计特性要求的热噪声数据,并将该数据放入估计样本集中;设置一个估计样本集,用于存放满足要求的热噪声数据;当估计样本集内数据的数目大于设定数量时,进行异常点的寻找并剔除异常点。当已剔除异常点的估计样本集的数据数目大于设定的阈值时,则可对热噪声的统计特性进行估计。The purpose of the present invention is to provide a device and method for searching thermal noise data in A/C and S mode overlapping signals. Swipe on , judge and find the thermal noise data that meets the statistical characteristics requirements, and put the data into the estimated sample set; set an estimated sample set to store the thermal noise data that meets the requirements; when the data in the estimated sample set When the number is greater than the set number, the abnormal point is searched and eliminated. When the number of data in the estimated sample set that has eliminated outliers is greater than the set threshold, the statistical characteristics of thermal noise can be estimated.

为实现上述目的,本发明提供了如下方案:To achieve the above object, the present invention provides the following scheme:

一种A/C和S模式交叠信号中寻找热噪声数据的装置,包括数据采集单元、数据处理单元和数据输出单元;所述数据采集单元用于采集A/C模式和S模式交叠信号中一段信号数据;所述数据处理单元用于将所述数据采集单元采集的信号数据进行处理,并发送到所述数据输出单元;所述数据输出单元用于将所述数据处理单元处理后的数据输出。A device for finding thermal noise data in overlapping signals of A/C and S modes, comprising a data acquisition unit, a data processing unit and a data output unit; the data acquisition unit is used to collect overlapping signals of A/C mode and S mode A section of signal data; the data processing unit is used to process the signal data collected by the data acquisition unit and send it to the data output unit; the data output unit is used to process the data processed by the data processing unit data output.

一种A/C模式和S模式交叠信号中寻找热噪声数据的方法,包括:A method for finding thermal noise data in A/C-mode and S-mode overlapping signals, comprising:

步骤201、采集A/C模式和S模式交叠信号中一段信号数据,定义循环次数I,初始化所述循环次数I为1;Step 201, collecting a section of signal data in the overlapping signal of A/C mode and S mode, defining the number of cycles I, and initializing the number of cycles I as 1;

步骤202、将所述信号数据存入数据滑动窗口;Step 202, storing the signal data into a data sliding window;

步骤203、删除所述数据滑动窗口内信号数据的脉冲的上升沿和下降沿;Step 203, delete the rising edge and falling edge of the pulse of the signal data in the data sliding window;

步骤204、将第三步得到的所述数据滑动窗口内信号数据按幅度值由小到大排序;Step 204, sort the signal data in the data sliding window obtained in the third step from small to large according to the amplitude value;

步骤205、判断所述循环次数是否为1,是执行步骤206,否执行步骤207;Step 205, judging whether the number of cycles is 1, if yes execute step 206, if no execute step 207;

步骤206、获取所述数据滑动窗口内前N个信号数据存入估计样本集,并删除所述数据滑动窗口内的所述前N个信号数据,N大于1且小于等于所述数据滑动窗口尺寸值;Step 206: Obtain the first N signal data in the data sliding window and store them in the estimated sample set, and delete the first N signal data in the data sliding window, where N is greater than 1 and less than or equal to the size of the data sliding window value;

步骤207、获取所述数据滑动窗口内的第1个值xw1,计算所述估计样本集的均值和标准差σnStep 207. Obtain the first value x w1 in the data sliding window, and calculate the mean value of the estimated sample set and standard deviation σ n ;

步骤208、判断是否大于cnσn,其中cn是定义常数,可设定为2.6~4,是删除所述数据滑动窗口内所有数据后执行步骤210,否执行步骤209;Step 208, judge Whether it is greater than c n σ n , where c n is a defined constant, which can be set to 2.6 to 4, and execute step 210 after deleting all data in the data sliding window, or execute step 209 if not;

步骤209、将所述xw1放入所述估计样本集内,并从所述数据滑动窗口内删除所述xw1,执行步骤207;Step 209, put the x w1 into the estimated sample set, and delete the x w1 from the data sliding window, and execute step 207;

步骤210、判断所述评估样本集的数据数目是否大于C1,C1是定义常数,C1可定义为大于10的整数,大于等于C1,则使用聚类中的异常点处理方法进行异常点去除处理得到异常点去除后的估计样本集内数据,再执行步骤211;小于C1,则所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤203;Step 210, judging whether the number of data in the evaluation sample set is greater than C1, C1 is a defined constant, C1 can be defined as an integer greater than 10, and greater than or equal to C1, then use the abnormal point processing method in clustering to perform abnormal point removal processing to obtain The data in the estimated sample set after the outliers are removed, then execute step 211; if it is less than C1, then the data sliding window spans the length of a data sliding window along the time axis, and then reloads new data; the number of cycles I Add 1, execute step 203;

步骤211、判断所述异常点去除后的估计样本集内数据数目是否大于C2,C2是定义常数,大于C2,则使用所述估计样本集内的数据进行热噪声的统计特性估计处理;小于C2,则所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤203;Step 211, judging whether the number of data in the estimated sample set after removing the outliers is greater than C2, C2 is a defined constant, and if it is greater than C2, use the data in the estimated sample set to perform statistical characteristic estimation processing of thermal noise; if it is less than C2 , then the data sliding window spans the length of a data sliding window along the time axis, and then reloads new data; the number of cycles I is increased by 1, and step 203 is performed;

步骤212、将所述估计样本集内的数据进行由小到大的排序,并将排序后的数据放入估计样本集内;删除所述估计样本集后面的C3个数据,C3是定义常数,得到新的估计样本集数据。Step 212, sort the data in the estimated sample set from small to large, and put the sorted data into the estimated sample set; delete C3 data behind the estimated sample set, C3 is a defined constant, Get the new estimated sample set data.

根据本发明提供的具体实施例,本发明公开了以下技术效果:According to the specific embodiments provided by the invention, the invention discloses the following technical effects:

本发明的一种A/C和S模式交叠信号中寻找热噪声数据的装置方法,可在任意长的A/C模式数据和噪声、S模式信号数据和噪声或A/C模式数据+S模式信号数据和噪声所构成的混合数据段中寻找出热噪声数据,该方法具有较好的实时性和自适应性,可以较好地实现热噪声统计特性的估计。实际中该方法可以不限于热噪声数据的寻找,还可发现杂波或具有随机性质数据的寻找。A device and method for finding thermal noise data in A/C and S mode overlapping signals of the present invention can be used in any length of A/C mode data and noise, S mode signal data and noise or A/C mode data+S The thermal noise data is found from the mixed data segment composed of model signal data and noise. This method has better real-time and adaptive properties, and can better estimate the statistical characteristics of thermal noise. In practice, this method is not limited to the search for thermal noise data, but also for finding clutter or data with random properties.

附图说明Description of drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施例中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required in the embodiments. Obviously, the accompanying drawings in the following description are only some of the present invention. Embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without paying creative labor.

图1为本发明一种A/C和S模式交叠信号中寻找热噪声数据的装置的结构示意图;Fig. 1 is the structural representation of the device that seeks thermal noise data in a kind of A/C and S mode overlapping signal of the present invention;

图2为本发明一种A/C和S模式交叠信号中寻找热噪声数据的方法的流程示意图。Fig. 2 is a schematic flowchart of a method for finding thermal noise data in A/C and S mode overlapping signals according to the present invention.

具体实施方式Detailed ways

下面将结合本发明实施例中的附图,对本发明实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

本发明的目的是提供一种A/C和S模式交叠信号中寻找热噪声数据的装置及方法,可在任意长的A/C模式数据和噪声、S模式信号数据和噪声或A/C模式数据+S模式信号数据和噪声所构成的混合数据段中寻找出热噪声数据,该方法具有较好的实时性和自适应性,可以较好地实现热噪声统计特性的估计。实际中该方法可以不限于热噪声数据的寻找,还可发现杂波或具有随机性质数据的寻找。The purpose of the present invention is to provide a kind of device and the method for looking for thermal noise data in A/C and S pattern overlapping signal, can be in arbitrary length A/C pattern data and noise, S pattern signal data and noise or A/C The thermal noise data is found in the mixed data segment composed of S-mode data + S-mode signal data and noise. This method has better real-time and adaptive properties, and can better estimate the statistical characteristics of thermal noise. In practice, this method is not limited to the search for thermal noise data, but also for finding clutter or data with random properties.

为使本发明的上述目的、特征和优点能够更加明显易懂,下面结合附图和具体实施方式对本发明作进一步详细的说明。In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

实施例:Example:

如图1、图2所示,一种A/C和S模式交叠信号中寻找热噪声数据的装置,包括数据采集单元(1)、数据处理单元(2)和数据输出单元(3);所述数据采集单元(1)用于采集A/C模式和S模式交叠信号中一段信号数据;所述数据处理单元(2)用于将所述数据采集单元(1)采集的信号数据进行处理,并发送到所述数据输出单元(3);所述数据输出单元(3)用于将所述数据处理单元(2)处理后的数据输出。As shown in Figure 1 and Figure 2, a device for searching thermal noise data in A/C and S mode overlapping signals, including a data acquisition unit (1), a data processing unit (2) and a data output unit (3); The data acquisition unit (1) is used to collect a segment of signal data in A/C mode and S mode overlapping signals; the data processing unit (2) is used to process the signal data collected by the data acquisition unit (1) processed, and sent to the data output unit (3); the data output unit (3) is used to output the data processed by the data processing unit (2).

一种A/C和S模式交叠信号中寻找热噪声数据的方法,包括:A method for finding thermal noise data in A/C and S mode overlapping signals, comprising:

步骤201、将一个整数变量定义为循环次数,并将循环次数的初始值设为1;设定两个数据集,一个是估计样本集,在初始设定时,估计样本集内无元素;一个是数据滑动窗口,数据滑动窗口包含了一段实时接收的数据(信号+噪声),数据滑动窗口可在所接收信号的数据序列上的任意位置开始;Step 201, define an integer variable as the number of cycles, and set the initial value of the number of cycles to 1; set two data sets, one is the estimated sample set, and when initially set, there is no element in the estimated sample set; one Is the data sliding window, the data sliding window contains a section of real-time received data (signal + noise), the data sliding window can start at any position on the data sequence of the received signal;

步骤202、将信号数据存入数据滑动窗口;Step 202, storing the signal data into the data sliding window;

步骤203、删除数据滑动窗口内脉冲的上升沿和下降沿。Step 203, delete the rising edge and falling edge of the pulse in the data sliding window.

步骤204、将数据滑动窗口中的数据进行由小到大的排序(幅度值)后,并重新放入数据滑动窗口。因为热噪声值一般都小于信号值,排序处理将热噪声数据和存在信号的数据分开:热噪声数据排在数据滑动窗口的前面,而存在信号的数据排在数据滑动窗口的后面,这有利于后续的处理;Step 204, after sorting the data in the data sliding window from small to large (amplitude values), and putting them into the data sliding window again. Because the thermal noise value is generally smaller than the signal value, the sorting process separates the thermal noise data and the data with the signal: the thermal noise data is sorted in front of the data sliding window, and the data with the signal is sorted behind the data sliding window, which is beneficial subsequent processing;

步骤205、判断所述循环次数是否为1,是执行步骤206,否执行步骤207;Step 205, judging whether the number of cycles is 1, if yes execute step 206, if no execute step 207;

步骤206、获取所述数据滑动窗口内前N个信号数据存入估计样本集,并删除所述数据滑动窗口内的所述前N个信号数据,N大于1且小于等于所述数据滑动窗口尺寸值;Step 206: Obtain the first N signal data in the data sliding window and store them in the estimated sample set, and delete the first N signal data in the data sliding window, where N is greater than 1 and less than or equal to the size of the data sliding window value;

步骤207、获取所述数据滑动窗口内的第1个值xw1,计算所述估计样本集的均值和标准差σnStep 207. Obtain the first value x w1 in the data sliding window, and calculate the mean value of the estimated sample set and standard deviation σ n ;

步骤208、判断是否大于cnσn,其中cn是定义常数,可设定为2.6~4,是删除所述数据滑动窗口内所有数据后执行步骤210,否执行步骤209;Step 208, judge Whether it is greater than c n σ n , where c n is a defined constant, which can be set to 2.6 to 4, and execute step 210 after deleting all data in the data sliding window, or execute step 209 if not;

步骤209、将所述xw1放入所述估计样本集内,并从所述数据滑动窗口内删除所述xw1;执行步骤207;Step 209, put the x w1 into the estimation sample set, and delete the x w1 from the data sliding window; execute step 207;

步骤210、判断所述评估样本集的数据数目是否大于C1,C1是定义常数,C1可定义为大于10的整数,大于等于C1,则使用聚类中的异常点处理方法进行异常点去除处理得到异常点去除后的估计样本集内数据,再执行步骤211;小于C1,则所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤203;Step 210, judging whether the number of data in the evaluation sample set is greater than C1, C1 is a defined constant, C1 can be defined as an integer greater than 10, and greater than or equal to C1, then use the abnormal point processing method in clustering to perform abnormal point removal processing to obtain The data in the estimated sample set after the outliers are removed, then execute step 211; if it is less than C1, then the data sliding window spans the length of a data sliding window along the time axis, and then reloads new data; the number of cycles I Add 1, execute step 203;

步骤211、将所述估计样本集内的数据进行由小到大的排序,并将排序后的数据放入估计样本集内;删除所述估计样本集后面的C3个数据,C3是定义常数,可定义为估计样本集内数据数目的1/10~1/3,得到新的估计样本集数据。所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤203;Step 211, sort the data in the estimated sample set from small to large, and put the sorted data into the estimated sample set; delete the C3 data behind the estimated sample set, C3 is a defined constant, It can be defined as 1/10 to 1/3 of the number of data in the estimated sample set to obtain new estimated sample set data. The data sliding window spans the length of a data sliding window along the time axis, and then reloads new data; the number of cycles I is increased by 1, and step 203 is performed;

步骤212、要使用估计样本集内数据的数据进行热噪声的统计特性估计处理,则估计样本集内数据数目需要大于C2,C2是定义常数,C2与所要求的的噪声特性的估计精度有关,可根据所要求的精度确定。Step 212: To use the data in the estimated sample set to estimate the statistical characteristics of thermal noise, the number of data in the estimated sample set needs to be greater than C2, where C2 is a defined constant, and C2 is related to the required estimation accuracy of noise characteristics. It can be determined according to the required accuracy.

上述步骤中cn、C1、C2、C3、N都是预先定义的正整数值。In the above steps, c n , C1, C2, C3, and N are all predefined positive integer values.

本文中应用了具体个例对本发明的原理及实施方式进行了阐述,以上实施例的说明只是用于帮助理解本发明的方法及其核心思想;同时,对于本领域的一般技术人员,依据本发明的思想,在具体实施方式及应用范围上均会有改变之处。综上所述,本说明书内容不应理解为对本发明的限制。In this paper, specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; meanwhile, for those of ordinary skill in the art, according to the present invention Thoughts, there will be changes in specific implementation methods and application ranges. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims (1)

1.一种A/C模式和S模式交叠信号中寻找热噪声数据的方法,其特征在于,包括步骤:1. A method for finding thermal noise data in A/C mode and S mode overlapping signal, it is characterized in that, comprises steps: 1)、采集A/C模式和S模式交叠信号中一段信号数据,定义循环次数I,初始化所述循环次数I为1;1), collecting a section of signal data in A/C mode and S mode overlapping signal, defining the number of cycles I, and initializing the number of cycles I to be 1; 2)、将所述信号数据存入数据滑动窗口;2), storing the signal data into the data sliding window; 3)、删除所述数据滑动窗口内信号数据的脉冲的上升沿和下降沿;3), delete the rising edge and falling edge of the pulse of the signal data in the data sliding window; 4)、将第3)步得到的所述数据滑动窗口内信号数据按幅度值由小到大排序;4), the signal data in the described data sliding window obtained in step 3) is sorted from small to large according to the amplitude value; 5)、判断所述循环次数是否为1,是执行步骤6,否执行步骤7;5), judging whether the number of cycles is 1, if it is to execute step 6, if not to execute step 7; 6)、获取所述数据滑动窗口内前N个信号数据存入估计样本集,并删除所述数据滑动窗口内的所述前N个信号数据,N大于1且小于等于所述数据滑动窗口尺寸值;6) Obtain the first N signal data in the data sliding window and store them in the estimated sample set, and delete the first N signal data in the data sliding window, where N is greater than 1 and less than or equal to the size of the data sliding window value; 7)、获取所述数据滑动窗口内的第1个值xw1,计算出所述估计样本集的均值和标准差σn7) Obtain the first value x w1 in the data sliding window, and calculate the mean value of the estimated sample set and standard deviation σ n ; 8)、判断|xw1-xn|是否大于cnσn,其中cn是2.6~4的常数,大于则删除所述数据滑动窗口内所有数据后执行步骤10,小于等于执行步骤9;8), judging whether |x w1 -x n | is greater than c n σ n , where c n is a constant of 2.6 to 4, if it is greater, delete all the data in the data sliding window and then perform step 10, if it is less than or equal to perform step 9; 9)、将所述xw1放入所述估计样本集内,并从所述数据滑动窗口内删除所述xw1,执行步骤7;9), put the x w1 into the estimated sample set, and delete the x w1 from the data sliding window, and perform step 7; 10)、判断所述估计样本集的数据数目是否大于C1,C1是大于10的整数,大于等于C1则使用聚类中的异常点处理方法进行异常点去除处理得到异常点去除后的估计样本集内数据,再执行步骤11,小于C1,则所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤3;10), judging whether the number of data in the estimated sample set is greater than C1, C1 is an integer greater than 10, if greater than or equal to C1, use the outlier processing method in clustering to perform outlier removal processing to obtain the estimated sample set after outlier removal In the data, step 11 is executed again, if it is less than C1, then the data sliding window spans the length of a data sliding window along the time axis, and then reloads new data; the number of cycles 1 is added by 1, and step 3 is executed; 11)、判断所述异常点去除后的估计样本集内数据数目是否大于C2,C2定义为与所要求的噪声特性的估计精度有关的常数,大于C2,则使用所述估计样本集内的数据进行热噪声的统计特性估计处理;小于等于C2,则所述数据滑动窗口沿着时间轴跨越一个数据滑动窗口的长度,再重新装入新的数据;所述循环次数I加1,执行步骤3;11), judging whether the number of data in the estimated sample set after the outlier removal is greater than C2, C2 is defined as a constant related to the estimation accuracy of the required noise characteristics, if it is greater than C2, then use the data in the estimated sample set Carry out the statistical characteristic estimation processing of thermal noise; Be less than or equal to C2, then described data sliding window spans the length of a data sliding window along time axis, reload new data again; Described number of cycles I adds 1, executes step 3 ; 12)、将所述估计样本集内的数据进行由小到大的排序,并将排序后的数据放入估计样本集内;删除所述估计样本集后面的C3个数据,C3定义为估计样本集内数据数目的1/10~1/3,得到新的估计样本集数据。12), sort the data in the estimated sample set from small to large, and put the sorted data into the estimated sample set; delete the C3 data behind the estimated sample set, and C3 is defined as the estimated sample 1/10 to 1/3 of the number of data in the set to obtain new estimated sample set data.
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