WO2019170000A1 - 一种频谱监测数据处理系统及方法 - Google Patents

一种频谱监测数据处理系统及方法 Download PDF

Info

Publication number
WO2019170000A1
WO2019170000A1 PCT/CN2019/075657 CN2019075657W WO2019170000A1 WO 2019170000 A1 WO2019170000 A1 WO 2019170000A1 CN 2019075657 W CN2019075657 W CN 2019075657W WO 2019170000 A1 WO2019170000 A1 WO 2019170000A1
Authority
WO
WIPO (PCT)
Prior art keywords
monitoring
spectrum
monitoring data
data
time
Prior art date
Application number
PCT/CN2019/075657
Other languages
English (en)
French (fr)
Inventor
游鸿
马红光
Original Assignee
西安大衡天成信息科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 西安大衡天成信息科技有限公司 filed Critical 西安大衡天成信息科技有限公司
Publication of WO2019170000A1 publication Critical patent/WO2019170000A1/zh

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16Spectrum analysis; Fourier analysis
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B17/00Monitoring; Testing
    • H04B17/30Monitoring; Testing of propagation channels
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B17/00Monitoring; Testing

Definitions

  • the invention belongs to the technical field of radio spectrum monitoring data processing, and particularly relates to a spectrum monitoring station monitoring data processing system and a data structure processing method.
  • the processing of electromagnetic spectrum monitoring data to obtain the detailed use of spectrum is the basis for rational and efficient spectrum resource utilization and spectrum management.
  • the traditional electromagnetic spectrum monitoring data processing method mainly uses a sequential relational database for storage and processing. Due to the natural mass and dispersion characteristics of spectrum monitoring data, the storage and processing methods of traditional spectrum monitoring data are gradually difficult to adapt to the new requirements for electromagnetic spectrum data transmission and big data processing.
  • the electromagnetic spectrum monitoring data has very distinct structural features.
  • the information of the time, frequency and position of the monitoring data is correlated. Therefore, for this feature, the time, frequency and level of the monitoring data will be monitored. ), location and other information are associated, and a new structured data processing system and method will be proposed, which will facilitate the transmission, storage and analysis of electromagnetic spectrum data.
  • the present invention provides a spectrum monitoring data processing system and method for the data processing requirements of the electromagnetic spectrum monitoring station, and utilizes the system and system proposed by the present invention.
  • the method can realize the normalized processing process of the spectrum monitoring data, form a data processing flow that meets the requirements of the spectrum monitoring network system, and gives a matrix representation of the monitoring data and its mathematical operation, which is beneficial to the monitoring data of multiple stations being more reasonable. And efficient use.
  • a spectrum monitoring data processing system comprising:
  • Station calibration and synchronization module for position calibration of spectrum monitoring stations, synchronous monitoring of clocks, determination of monitoring time points, determination of monitoring spectrum sampling points and spectrum bandwidth requirements;
  • the monitoring data preprocessing module is configured to complete the discretization of the monitoring data for a given sampling time and the structured data processing of the given period of time;
  • a monitoring data compression processing module for performing overall compression processing of monitoring data for a given period of time
  • a data sending module for transmitting compressed data to a central station, a data center, or other relay station.
  • the station calibration and synchronization module includes:
  • the spectrum monitoring station position calibration unit is configured to obtain the accurate position information of the spectrum monitoring station by using the satellite navigation and positioning module, and the position information is used to identify the position information of the spectrum monitoring data;
  • the monitoring time calibration unit is configured to calibrate the monitoring station's own clock by using a network, an atomic clock or a satellite navigation timing module.
  • the time-calibrated station can accurately identify the station data in the time dimension and realize multiple stations according to the time. Unified time step for monitoring;
  • the monitoring parameter synchronization unit is configured to synchronously acquire initial parameters of spectrum monitoring sent by the central station or the data center, such as sampling time period, monitoring data sampling interval, monitored frequency band, monitoring spectrum sampling number, etc., and these monitoring parameters can be used Discretization and normalization of monitoring data.
  • the initial parameters of the spectrum monitoring include a sampling period, a monitoring data sampling interval, a monitored frequency band, and a monitoring spectrum sampling number.
  • the monitoring data preprocessing module includes:
  • the sampling time data discretization unit is configured to perform discretization of the monitoring data for a given sampling time, and obtain a one-dimensional spectrum monitoring sequence at a given sampling time according to the required number of spectral sampling points within a given spectral bandwidth.
  • the time period monitoring data structure processing unit is configured to arrange the spectrum monitoring series of different sampling times according to the time interval of the monitoring data in a given monitoring time period to form a two-dimensional spectrum matrix.
  • the matrix W is N x M dimensions.
  • the monitoring data compression processing module performs compression processing on a spectrum matrix composed of monitoring data for a given period of time by the following steps:
  • the invention also provides a spectrum monitoring data processing method, comprising the following steps:
  • S1 spectrum monitoring station calibration, complete monitoring station position calibration V, synchronous monitoring clock t, synchronous monitoring time point t n , monitoring spectrum sampling point M and spectrum bandwidth B, where n takes 0, 1, 2, ..., N, N is a positive integer;
  • monitoring data pre-processing completing discretization of monitoring data at a given time and structured data processing of monitoring data for a given monitoring period, obtaining a one-dimensional spectrum monitoring sequence at a given sampling time And a two-dimensional spectrum matrix W for a given monitoring period;
  • S4 Data transmission, transmitting the compressed data to a central station, a data center or other relay station.
  • the monitoring data preprocessing comprises the following steps:
  • S2.2 Discretize the data according to the required number of spectral sampling points M in a given spectral bandwidth B, and obtain a one-dimensional spectrum monitoring sequence at a given sampling time sequence Is 1 ⁇ M dimension;
  • Each two-dimensional spectrum matrix W is additionally provided with monitoring information, including monitoring station position information, sampling time and interval, and frequency band.
  • the monitoring data compression process includes the following steps.
  • the data sending includes the following steps:
  • S4.3 station position, sampling time and interval, and frequency band information corresponding to the two-dimensional spectrum matrix W.
  • the invention also provides a spectrum monitoring data processing method, comprising the following steps:
  • S2 Discretize the spectrum monitoring data of the station at a given time with the required number of spectral sampling points M, and obtain a one-dimensional spectrum monitoring sequence at a given sampling time. sequence 1 ⁇ M dimension, aligning the 1D spectrum monitoring sequence at different sampling times according to chronological order Obtain a two-dimensional spectrum matrix for a given monitoring period
  • the matrix W is N ⁇ M dimensions;
  • each two-dimensional spectrum matrix It also includes monitoring station location information, sampling time, sampling interval, and frequency band information.
  • step S3 includes:
  • the compressed data includes:
  • the station position, sampling time, sampling interval, and frequency band information corresponding to the two-dimensional spectrum matrix W is a station position, sampling time, sampling interval, and frequency band information corresponding to the two-dimensional spectrum matrix W.
  • the invention has the beneficial effects that the spectrum monitoring data processing system of the present invention can unify the normalized processing process of the spectrum monitoring data, form a data processing flow that meets the requirements of the spectrum monitoring network system, and A matrix representation of the monitoring data and its mathematical operations are beneficial to the more reasonable and efficient use of monitoring data by multiple stations.
  • FIG. 1 is a schematic diagram of an application scenario of a spectrum monitoring data processing system according to the present invention.
  • FIG. 2 is a structural block diagram of the composition of the spectrum monitoring data processing system of the present invention.
  • FIG. 3 is a schematic diagram of a spectrum matrix of spectrum monitoring data of the present invention.
  • FIG. 4 is an example of the value of the monitoring data collected by the spectrum analyzer in a time-frequency two-dimensional space.
  • Figure 5 is a grayscale diagram of the spectrum matrix of the spectrum monitoring data of a station.
  • FIG. 1 is a schematic diagram of an application scenario of a spectrum monitoring data processing system according to an embodiment of the present invention.
  • FIG. 2 is a structural block diagram of the composition of the spectrum monitoring data processing system of the present invention.
  • the spectrum monitoring data processing system of the present invention comprises a station calibration module, a monitoring data preprocessing module, a monitoring data compression processing module, and a data transmission module.
  • the station calibration module is used for position calibration of the spectrum monitoring station, synchronous monitoring clock, synchronous monitoring time point, determining monitoring spectrum sampling point, spectrum bandwidth requirement; monitoring data preprocessing module for completing monitoring at a given time Data discretization and structured processing of monitoring data for a given monitoring period; monitoring data compression processing module for completing overall compression processing of monitoring data in a given time period; data transmitting module for transmitting compressed data to a central station , data center or other relay station.
  • the station calibration module in the spectrum monitoring data processing system includes a spectrum monitoring station position calibration unit, a monitoring time calibration unit, and a monitoring parameter synchronization unit.
  • the spectrum monitoring station position calibration unit is configured to obtain the accurate position information of the spectrum monitoring station by using the satellite navigation positioning module, the position information is used to identify the position information of the spectrum monitoring data; the monitoring time calibration unit is used to utilize the network,
  • the atomic clock or satellite navigation timing module calibrates the monitoring station's own clock.
  • the time-calibrated station can accurately identify the station data in the time dimension and realize the monitoring of multiple stations according to the uniform time step; monitoring parameter synchronization
  • the unit is used for synchronously acquiring initial parameters of spectrum monitoring sent by the central station or the data center, such as sampling time period, monitoring data sampling interval, monitored frequency band, monitoring spectrum sampling number, etc., and these monitoring parameters can be used to discretize and Standardize monitoring data.
  • the monitoring data preprocessing module in the spectrum monitoring data processing system includes a sampling time data discretization unit and a period monitoring data structure processing unit.
  • the sampling time data discretization unit is configured to perform discretization of the monitoring data for a given sampling time, and obtain a one-dimensional spectrum monitoring sequence at a given sampling time according to the required number of spectral sampling points within a given spectral bandwidth;
  • the monitoring data structure processing unit is configured to arrange the spectrum monitoring sequences of different sampling times according to the time interval of the monitoring data in a given monitoring time period to form a two-dimensional spectrum matrix.
  • a monitoring data compression processing module in the spectrum monitoring data processing system is configured to compress a spectrum matrix composed of monitoring data for a given period of time.
  • the spectrum monitoring data processing method of the present invention comprises the following steps:
  • S1 spectrum monitoring station calibration, complete monitoring station position calibration V, synchronous monitoring time t, synchronous monitoring time point t n (0...N), monitoring spectrum sampling point M and spectrum bandwidth B;
  • monitoring data pre-processing completing discretization of monitoring data at a given time and structured data processing of monitoring data for a given monitoring period, obtaining a one-dimensional spectrum monitoring sequence at a given sampling time And a two-dimensional spectrum matrix W for a given monitoring period;
  • S4 Data transmission, transmitting the compressed data to a central station, a data center or other relay station.
  • the monitoring data preprocessing comprises the following steps:
  • S2.2 Discretize the data according to the required number of spectral sampling points M in a given spectral bandwidth B, and obtain a one-dimensional spectrum monitoring sequence at a given sampling time sequence Is 1 ⁇ M dimension;
  • S2.5 Each two-dimensional spectrum matrix W, with additional monitoring information, including monitoring station location information, sampling time and interval, frequency band, and the like.
  • the monitoring data compression processing includes the following steps:
  • the image processing method is applied to the grayscale image G for compression processing.
  • the compression method can be JPEG or JPEG 2000.
  • step S4 data transmission of the above spectrum monitoring data processing method, the following steps are included:
  • S4.3 information such as station position, sampling time and interval, and frequency band corresponding to the two-dimensional spectrum matrix W.
  • Figure 4 shows an example of time-frequency two-dimensional space acquisition of spectrum monitoring data obtained somewhere in Linyi using a spectrum analyzer.
  • the time domain takes 50 sampling moments, the sampling bandwidth is 500 MHz, and the sampling points in the frequency domain are 501.
  • the spectrum matrix W is 50 x 501 dimensions.
  • FIG. 5 is a grayscale diagram of a spectral matrix obtained by mapping the data of FIG. 4 to an 8-order gray scale.

Landscapes

  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mathematical Physics (AREA)
  • General Physics & Mathematics (AREA)
  • Monitoring And Testing Of Transmission In General (AREA)

Abstract

一种频谱监测数据处理系统,包括:台站校准与同步模块、监测数据预处理模块、监测数据压缩处理模块、数据发送模块;以及一种频谱监测数据处理方法,包括以下步骤:台站校准,包括频谱监测台站位置信息校准、同步监测时间;监测数据预处理,包括给定时刻监测数据离散化和给定监测时段监测数据结构化处理;监测数据压缩处理,完成给定时段内监测数据的整体压缩处理;数据发送,将压缩后的数据传输给中心台站或数据中心。该方案能够统一频谱监测数据的规范化处理过程,形成符合频谱监测网系要求的数据处理流程,并且给出了一种监测数据的矩阵表示及其数学运算,有利于多台站监测数据被更加合理和高效的利用。

Description

一种频谱监测数据处理系统及方法 技术领域
本发明属于无线电频谱监测数据处理技术领域,特别涉及一种频谱监测台站监测数据处理系统及数据结构化处理方法。
背景技术
随着频谱资源重要性和重视程度的提高,电磁频谱台站数量的急剧扩大,对电磁频谱监测数据处理以获取频谱使用详细状况是合理和高效进行频谱资源利用和频谱管理的基础。尤其是随着频谱网系建设的发展,频谱监测台站及不同频谱管理单位间的数据传输和处理需求不断提高,对频谱监测数据进行深度挖掘,采用大数据方法获取更多信息的要求也非常迫切。传统的电磁频谱监测数据处理方法主要是采用序贯式的关系型数据库来进行存储和处理。由于频谱监测数据具有天然的海量、分散的特点,使得传统频谱监测数据的存储和处理方法渐渐难以适应对电磁频谱数据传输和大数据处理新要求。
实际上,电磁频谱监测数据具有非常鲜明的结构化特征,监测数据的时间、频率和位置等维度的信息具有相关性,因此,针对这种特点,将监测数据的时间、频率、电平(幅度)、位置等信息关联起来,提出新的结构化数据处理系统和方法,将有利于电磁频谱数据的传输、存储和分析。
发明内容
为了克服上述现有技术的缺点,在借鉴和发展方法和理论的基础上,本发明针对电磁频谱监测台站数据处理需求,提供一种频谱监测数据处理系统及方法,利用本发明提出的系统和方法,能够实现频谱监测数据的规范化处理过程,形成符合频谱监测网系要求的数据处理流程,并且给出了一种监测数据的矩阵表示及其数学运算,有利于多台站监测数据被更加合理和高效的利用。
为了实现上述目的,本发明采用的技术方案是:
一种频谱监测数据处理系统,包括:
台站校准与同步模块,用于对频谱监测台站位置校准,同步监测时钟,确定 监测时间点,确定监测频谱采样点和频谱带宽要求;
监测数据预处理模块,用于完成对给定采样时刻监测数据离散化和给定时段监测数据结构化处理;
监测数据压缩处理模块,用于完成给定时段监测数据的整体压缩处理;
数据发送模块,用于将压缩后的数据传输给中心台站、数据中心或其他中继台站。
进一步地,所述台站校准与同步模块包括:
频谱监测台站位置校准单元,用于利用卫星导航定位模块获取频谱监测台站自身准确位置信息,该位置信息用来标识频谱监测数据的位置信息;
监测时间校准单元,用于利用网络、原子钟或卫星导航授时模块校准监测台站自身的时钟,经过时间校准的台站,可以实现对台站数据在时间维度上进行准确标识并实现多台站按照统一时间步长进行监测;
监测参数同步单元,用于同步获取中心台站或数据中心发来的频谱监测初始参数,例如采样时间段、监测数据采样间隔、监测的频段、监测频谱采样数等信息,这些监测参数可以用来离散化和规范化监测数据。
所述频谱监测初始参数包括采样时间段、监测数据采样间隔、监测的频段以及监测频谱采样数。
进一步地,所述监测数据预处理模块包括:
采样时刻数据离散化单元,用于完成对给定采样时刻监测数据离散化,在给定的频谱带宽内,按照要求的频谱采样点数,获取给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000001
数列
Figure PCTCN2019075657-appb-000002
为1×M维;
时段监测数据结构化处理单元,用于在给定的监测时间段内,按照监测数据时间采样间隔,按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵
Figure PCTCN2019075657-appb-000003
矩阵W为N×M维。
所述监测数据压缩处理模块通过如下步骤对,给定时段监测数据组成的频谱矩阵进行压缩处理:
S3.1:获取二维频谱矩阵
Figure PCTCN2019075657-appb-000004
的最大值和最小值;
S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
S3.3:对灰度图G采用图像压缩方法进行压缩处理。
本发明同时提供了一种频谱监测数据处理方法,包括以下步骤:
S1:频谱监测台站校准,完成监测台站位置校准V,同步监测时钟t、同步监测时间点t n、监测频谱采样点M以及频谱带宽B,其中n取0、1、2、……、N,N为正整数;
S2:监测数据预处理,完成给定时刻监测数据离散化和给定监测时段监测数据结构化处理,获取给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000005
和给定的监测时间段的二维频谱矩阵W;
S3:监测数据压缩处理,完成给定时段内监测数据W的整体压缩处理;
S4:数据发送,将压缩后的数据传输给中心台站、数据中心或其他中继台站。
进一步地,所述步骤S2中,所述监测数据预处理包括以下步骤:
S2.1:获取采样时刻t n频谱监测数据;
S2.2:在给定的频谱带宽B内,按照要求的频谱采样点数M,对数据进行离散化,获取给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000006
数列
Figure PCTCN2019075657-appb-000007
为1×M维;
S2.3:给定的监测时间段,按照监测数据时间采样间隔,获取不同采样时刻频谱监测数列
Figure PCTCN2019075657-appb-000008
S2.4:按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵
Figure PCTCN2019075657-appb-000009
矩阵W为N×M维;
S2.5:每个二维频谱矩阵W,额外附带监测信息,包括监测台站位置信息、采样时间及间隔、频带。
进一步地,所述步骤S3中,所述监测数据压缩处理包括以下步骤
S3.1:获取二维频谱矩阵
Figure PCTCN2019075657-appb-000010
的最大值和最小值。
S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
S3.3:对灰度图G采用图像压缩方法进行压缩处理。
进一步地,所述步骤S4中,所述数据发送包括以下步骤:
S4.1:压缩后的灰度图G;
S4.2:G对应的二维频谱矩阵W的最大值、最小值;
S4.3:二维频谱矩阵W对应的台站位置、采样时间及间隔、频带信息。
本发明同时提供了一种频谱监测数据处理方法,包括以下步骤:
S1:对监测台站位置进行校准V,同步监测时钟t、同步监测时间点t n、监测频谱采样点M以及频谱带宽B,其中n取0、1、2、……、N,N为正整数;
S2:将给定时刻的台站的频谱监测数据,以要求的频谱采样点数M,进行离散化,获得给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000011
数列
Figure PCTCN2019075657-appb-000012
为1×M维,根据时间顺序排列不同采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000013
获得给定的监测时间段的二维频谱矩阵
Figure PCTCN2019075657-appb-000014
矩阵W为N×M维;
S3:对所述给定时段内的频谱监测数据W进行压缩。
进一步,每个二维频谱矩阵
Figure PCTCN2019075657-appb-000015
还包括监测台站位置信息、采样时间、采样间隔和频带信息。
进一步,所述步骤S3中包括:
S3.1:获取二维频谱矩阵
Figure PCTCN2019075657-appb-000016
的最大值和最小值;
S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
S3.3:对灰度图G采用图像压缩方法进行压缩处理。
进一步,所述压缩后的数据包括:
压缩后的灰度图G;
灰度图G对应的二维频谱矩阵W的最大值、最小值;
二维频谱矩阵W对应的台站位置、采样时间、采样间隔和频带信息。
与现有技术相比,本发明的有益效果是:本发明所述一种频谱监测数据处理系统能够统一频谱监测数据的规范化处理过程,形成符合频谱监测网系要求的数据处理流程,并且给出了一种监测数据的矩阵表示及其数学运算,有利于多台站监测数据被更加合理和高效的利用。
附图说明
图1为本发明所述频谱监测数据处理系统应用场景示意图。
图2为本发明所述频谱监测数据处理系统组成的结构框图。
图3为本发明频谱监测数据频谱矩阵示意图。
图4为利用频谱分析仪采集到的监测数据在时间-频率二维空间取值示例。
图5为某台站频谱监测数据频谱矩阵灰度图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚,下面将结合本发明实施例中附图,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。通常在此处附图中描述和出示的本发明实施例的组件可以以各种不同的配置来布置和设计。因此,以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围,而是仅仅表示本发明的选定实施例。基于本发明的实施例,本领域技术人员在没有做出创造性劳动的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。
本发明主要应用台站频谱监测数据的压缩、传输,有利于多台站监测数据被更加合理和高效的利用。图1为本发明实施例所提供的一种频谱监测数据处理系统应用场景示意图。
图2为本发明所述频谱监测数据处理系统组成的结构框图。
参照图2,本发明频谱监测数据处理系统,包括台站校准模块、监测数据预处理模块、监测数据压缩处理模块、数据发送模块。其中,台站校准模块,用于对频谱监测台站位置校准、同步监测时钟、同步监测时间点、确定监测频谱采样点、频谱带宽要求;监测数据预处理模块,用于完成对给定时刻监测数据离散化和给定监测时段监测数据结构化处理;监测数据压缩处理模块,用于完成给定时段内监测数据的整体压缩处理;数据发送模块,用于将压缩后的数据传输给中心台站、数据中心或其他中继台站。
频谱监测数据处理系统中的台站校准模块包括频谱监测台站位置校准单元、监测时间校准单元、监测参数同步单元。其中,频谱监测台站位置校准单元,用于利用卫星导航定位模块获取频谱监测台站自身准确位置信息,该位置信息用来标识频谱监测数据的位置信息;监测时间校准单元,用于利用网络、原子钟或卫星导航授时模块校准监测台站自身的时钟,经过时间校准的台站,可以 实现对台站数据在时间维度上进行准确标识并实现多台站按照统一时间步长进行监测;监测参数同步单元,用于同步获取中心台站或数据中心发来的频谱监测初始参数,例如采样时间段、监测数据采样间隔、监测的频段、监测频谱采样数等信息,这些监测参数可以用来离散化和规范化监测数据。
频谱监测数据处理系统中的监测数据预处理模块包括采样时刻数据离散化单元和时段监测数据结构化处理单元。其中,采样时刻数据离散化单元,用于完成对给定采样时刻监测数据离散化,在给定的频谱带宽内,按照要求的频谱采样点数,获取给定采样时刻的一维频谱监测数列;时段监测数据结构化处理单元,用于在给定的监测时间段内,按照监测数据时间采样间隔,按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵。
频谱监测数据处理系统中的监测数据压缩处理模块,用于对给定时段监测数据组成的频谱矩阵进行压缩处理。
基于频谱监测数据处理系统,本发明频谱监测数据处理方法,包括以下步骤:
S1:频谱监测台站校准,完成监测台站位置校准V、同步监测时间t、同步监测时间点t n(0…N)、监测频谱采样点M以及频谱带宽B等参数;
S2:监测数据预处理,完成给定时刻监测数据离散化和给定监测时段监测数据结构化处理,获取给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000017
和给定的监测时间段的二维频谱矩阵W;
S3:监测数据压缩处理,完成给定时段内监测数据W的整体压缩处理;
S4:数据发送,将压缩后的数据传输给中心台站、数据中心或其他中继台站。
在上述一种频谱监测数据处理方法的步骤S2监测数据预处理中包括以下步骤:
S2.1:获取采样时刻t n频谱监测数据;
S2.2:在给定的频谱带宽B内,按照要求的频谱采样点数M,对数据进行离散化,获取给定采样时刻的一维频谱监测数列
Figure PCTCN2019075657-appb-000018
数列
Figure PCTCN2019075657-appb-000019
为1×M维;
S2.3:给定的监测时间段,按照监测数据时间采样间隔,获取不同采样时刻频谱监测数列
Figure PCTCN2019075657-appb-000020
S2.4:按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵
Figure PCTCN2019075657-appb-000021
矩阵W为N×M维。
S2.5:每个二维频谱矩阵W,额外附带监测信息,包括监测台站位置信息、采样时间及间隔、频带等。
在上述一种频谱监测数据处理方法的步骤S3监测数据压缩处理中包括以下步骤:
S3.1:获取二维频谱矩阵
Figure PCTCN2019075657-appb-000022
的最大值和最小值。
S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
S3.3:对灰度图G采用图像压缩方法进行压缩处理。压缩方法可以选择JPEG或JPEG 2000。
在上述一种频谱监测数据处理方法的步骤S4数据发送中包括以下步骤:
S4.1:压缩后的灰度图G;
S4.2:G对应的二维频谱矩阵W的最大值、最小值;
S4.3:二维频谱矩阵W对应的台站位置、采样时间及间隔、频带等信息。
图4为利用频谱分析仪在临潼某处获得的频谱监测数据在时间-频率二维空间取值实例,时间域取了50个采样时刻,采样带宽是500MHz,频率域采样点数是501,频谱矩阵W为50×501维。
图5为将图4数据映射为8阶灰度得到的频谱矩阵灰度图。

Claims (13)

  1. 一种频谱监测数据处理系统,其特征在于,包括:
    台站校准与同步模块,用于对频谱监测台站位置校准,同步监测时钟,确定监测时间点,确定监测频谱采样点和频谱带宽要求;
    监测数据预处理模块,用于完成对给定采样时刻监测数据离散化和给定时段监测数据结构化处理;
    监测数据压缩处理模块,用于完成给定时段监测数据的整体压缩处理;
    数据发送模块,用于将压缩后的数据传输给中心台站、数据中心或其他中继台站。
  2. 根据权利要求1所述频谱监测数据处理系统,其特征在于,所述台站校准与同步模块包括:
    频谱监测台站位置校准单元,用于利用卫星导航定位模块获取频谱监测台站自身准确位置信息;
    监测时间校准单元,用于利用网络、原子钟或卫星导航授时模块校准监测台站自身的时钟;
    监测参数同步单元,用于同步获取中心台站或数据中心发来的频谱监测初始参数。
  3. 根据权利要求2所述频谱监测数据处理系统,其特征在于,所述频谱监测初始参数包括采样时间段、监测数据采样间隔、监测的频段以及监测频谱采样数。
  4. 根据权利要求1所述频谱监测数据处理系统,其特征在于,所述监测数据预处理模块包括:
    采样时刻数据离散化单元,用于完成对给定采样时刻监测数据离散化,在给定的频谱带宽内,按照要求的频谱采样点数,获取给定采样时刻的一维频谱监测数列
    Figure PCTCN2019075657-appb-100001
    数列
    Figure PCTCN2019075657-appb-100002
    为1×M维;
    时段监测数据结构化处理单元,用于在给定的监测时间段内,按照监测数据时间采样间隔,按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵
    Figure PCTCN2019075657-appb-100003
    矩阵W为N×M维。
  5. 根据权利要求4所述频谱监测数据处理系统,其特征在于,所述监测数 据压缩处理模块通过如下步骤对,给定时段监测数据组成的频谱矩阵进行压缩处理:
    S3.1:获取二维频谱矩阵
    Figure PCTCN2019075657-appb-100004
    的最大值和最小值;
    S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
    S3.3:对灰度图G采用图像压缩方法进行压缩处理。
  6. 一种频谱监测数据处理方法,其特征在于,包括以下步骤:
    S1:频谱监测台站校准,完成监测台站位置校准V,同步监测时钟t、同步监测时间点t n、监测频谱采样点M以及频谱带宽B,其中n取0、1、2、……、N,N为正整数;
    S2:监测数据预处理,完成给定时刻监测数据离散化和给定监测时段监测数据结构化处理,获取给定采样时刻的一维频谱监测数列
    Figure PCTCN2019075657-appb-100005
    和给定的监测时间段的二维频谱矩阵W;
    S3:监测数据压缩处理,完成给定时段内监测数据W的整体压缩处理;
    S4:数据发送,将压缩后的数据传输给中心台站、数据中心或其他中继台站。
  7. 根据权利要求6所述频谱监测数据处理方法,其特征在于,所述步骤S2中,所述监测数据预处理包括以下步骤:
    S2.1:获取采样时刻t n频谱监测数据;
    S2.2:在给定的频谱带宽B内,按照要求的频谱采样点数M,对数据进行离散化,获取给定采样时刻的一维频谱监测数列
    Figure PCTCN2019075657-appb-100006
    数列
    Figure PCTCN2019075657-appb-100007
    为1×M维;
    S2.3:给定的监测时间段,按照监测数据时间采样间隔,获取不同采样时刻频谱监测数列
    Figure PCTCN2019075657-appb-100008
    S2.4:按照时间先后顺序将不同采样时刻频谱监测数列进行排列,组成二维频谱矩阵
    Figure PCTCN2019075657-appb-100009
    矩阵W为N×M维;
    S2.5:每个二维频谱矩阵W,额外附带监测信息,包括监测台站位置信息、采样时间及间隔、频带。
  8. 根据权利要求7所述频谱监测数据处理方法,其特征在于,所述步骤 S3中,所述监测数据压缩处理包括以下步骤
    S3.1:获取二维频谱矩阵
    Figure PCTCN2019075657-appb-100010
    的最大值和最小值。
    S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
    S3.3:对灰度图G采用图像压缩方法进行压缩处理。
  9. 根据权利要求8所述频谱监测数据处理方法,其特征在于,所述步骤S4中,所述数据发送包括以下步内容:
    S4.1:压缩后的灰度图G;
    S4.2:G对应的二维频谱矩阵W的最大值、最小值;
    S4.3:二维频谱矩阵W对应的台站位置、采样时间及间隔、频带信息。
  10. 一种频谱监测数据处理方法,其特征在于,包括以下步骤:
    S1:对监测台站位置进行校准V,同步监测时钟t、同步监测时间点t n、监测频谱采样点M以及频谱带宽B,其中n取0、1、2、……、N,N为正整数;
    S2:将给定时刻的台站的频谱监测数据,以要求的频谱采样点数M,进行离散化,获得给定采样时刻的一维频谱监测数列
    Figure PCTCN2019075657-appb-100011
    数列
    Figure PCTCN2019075657-appb-100012
    为1×M维,根据时间顺序排列不同采样时刻的一维频谱监测数列
    Figure PCTCN2019075657-appb-100013
    获得给定的监测时间段的二维频谱矩阵
    Figure PCTCN2019075657-appb-100014
    矩阵W为N×M维;
    S3:对所述给定时段内的频谱监测数据W进行压缩。
  11. 根据权利要求10所述频谱监测数据处理方法,其特征在于,
    每个二维频谱矩阵
    Figure PCTCN2019075657-appb-100015
    还包括监测台站位置信息、采样时间、采样间隔和频带信息。
  12. 根据权利要求10所述频谱监测数据处理方法,其特征在于,所述步骤S3中包括:
    S3.1:获取二维频谱矩阵
    Figure PCTCN2019075657-appb-100016
    的最大值和最小值;
    S3.2:将二维频谱矩阵W映射为一定位数的灰度图G;
    S3.3:对灰度图G采用图像压缩方法进行压缩处理。
  13. 根据权利要求12所述频谱监测数据处理方法,其特征在于,所述压缩后的数据包括:
    压缩后的灰度图G;
    灰度图G对应的二维频谱矩阵W的最大值、最小值;
    二维频谱矩阵W对应的台站位置、采样时间、采样间隔和频带信息。
PCT/CN2019/075657 2018-03-06 2019-02-21 一种频谱监测数据处理系统及方法 WO2019170000A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201810181412.8 2018-03-06
CN201810181412.8A CN108732423A (zh) 2018-03-06 2018-03-06 一种频谱监测数据处理系统及方法

Publications (1)

Publication Number Publication Date
WO2019170000A1 true WO2019170000A1 (zh) 2019-09-12

Family

ID=63940315

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/075657 WO2019170000A1 (zh) 2018-03-06 2019-02-21 一种频谱监测数据处理系统及方法

Country Status (2)

Country Link
CN (1) CN108732423A (zh)
WO (1) WO2019170000A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108732423A (zh) * 2018-03-06 2018-11-02 西安大衡天成信息科技有限公司 一种频谱监测数据处理系统及方法
US20200400730A1 (en) * 2018-03-06 2020-12-24 Xi'an Daheng Tiancheng It Co., Ltd. Frequency spectrum monitoring data structured representation method, and data processing method and compression method
CN111769891B (zh) * 2020-06-16 2022-08-26 西安大衡天成信息科技有限公司 一种基于张量分解的频谱监测大数据处理系统及处理方法

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09307880A (ja) * 1996-05-20 1997-11-28 Fujitsu General Ltd 無線監視システム
CN103957065A (zh) * 2014-05-20 2014-07-30 成都瀚德科技有限公司 全时频谱监测方法
CN103987117A (zh) * 2014-04-28 2014-08-13 北京邮电大学 一种基于移动终端监测的信号发射台站定位方法
CN106100776A (zh) * 2016-08-31 2016-11-09 成都九华圆通科技发展有限公司 基于无线台站网格监测系统的频谱感知方法
CN107171744A (zh) * 2017-06-30 2017-09-15 北京世纪德辰通信技术有限公司 一种基于三维地图的大功率台站开场测试系统及方法
CN108509506A (zh) * 2018-03-06 2018-09-07 西安大衡天成信息科技有限公司 一种频谱监测数据结构化表示方法
CN108616720A (zh) * 2018-03-06 2018-10-02 西安大衡天成信息科技有限公司 一种多台站频谱监测数据压缩处理方法
CN108732423A (zh) * 2018-03-06 2018-11-02 西安大衡天成信息科技有限公司 一种频谱监测数据处理系统及方法

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09307880A (ja) * 1996-05-20 1997-11-28 Fujitsu General Ltd 無線監視システム
CN103987117A (zh) * 2014-04-28 2014-08-13 北京邮电大学 一种基于移动终端监测的信号发射台站定位方法
CN103957065A (zh) * 2014-05-20 2014-07-30 成都瀚德科技有限公司 全时频谱监测方法
CN106100776A (zh) * 2016-08-31 2016-11-09 成都九华圆通科技发展有限公司 基于无线台站网格监测系统的频谱感知方法
CN107171744A (zh) * 2017-06-30 2017-09-15 北京世纪德辰通信技术有限公司 一种基于三维地图的大功率台站开场测试系统及方法
CN108509506A (zh) * 2018-03-06 2018-09-07 西安大衡天成信息科技有限公司 一种频谱监测数据结构化表示方法
CN108616720A (zh) * 2018-03-06 2018-10-02 西安大衡天成信息科技有限公司 一种多台站频谱监测数据压缩处理方法
CN108732423A (zh) * 2018-03-06 2018-11-02 西安大衡天成信息科技有限公司 一种频谱监测数据处理系统及方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
GUO YONGMING: "Time frequency based signal detection methods and their application in spectrum monitoring", XIDIAN UNIVERSITY DOCTORIAL DISSERTATION'S THESES, no. 04, 30 April 2011 (2011-04-30) *

Also Published As

Publication number Publication date
CN108732423A (zh) 2018-11-02

Similar Documents

Publication Publication Date Title
WO2019170000A1 (zh) 一种频谱监测数据处理系统及方法
Lord Estimation of parameters from incomplete data
CN107818120B (zh) 基于大数据的数据处理方法和装置
US11082059B1 (en) Method and system for obtaining and storing sensor data
CN111338814A (zh) 消息处理方法和装置、存储介质和电子装置
WO2016101464A1 (zh) 用户体验质量QoE评估方法、装置、终端及服务器
CN110350993B (zh) 一种大数据场景下基于联网监测的黑广播自动发现方法
CN113502870B (zh) 挖掘机工况判定方法及装置
US20210392523A1 (en) Tensor Decomposition-Based Big Data Processing System and Processing method for Spectrum Monitoring
CN109344034A (zh) 一种用于管理日志的方法和装置
CN110995273A (zh) 电力数据库的数据压缩方法、装置、设备及介质
CN109379698B (zh) 基于信道模型特征提取的小区测量报告定位方法及系统
WO2019170001A1 (zh) 一种频谱监测数据结构化表示方法、数据处理方法和压缩方法
CN110765025A (zh) 测试方法、装置、计算机设备及存储介质
CN103177189B (zh) 一种众源位置签到数据质量分析方法
Hongqian et al. Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms
CN113419872B (zh) 一种应用系统接口集成系统、集成方法、设备及存储介质
CN108616720B (zh) 一种多台站频谱监测数据压缩处理方法
CN109359707A (zh) 岩土样品信息的处理方法、装置、计算机设备和存储介质
CN108712306A (zh) 一种信息系统自动化巡检平台和巡检方法
US11281611B2 (en) General purpose interface bus (GPIB) sniffer system and method
CN102630092A (zh) 一种融入小波变换和主成分的农业无线传感数据流压缩方法
WO2016061964A1 (zh) Rohc压缩器的ir态回迁周期选择方法、装置和存储介质
CN111931080A (zh) 一种多时区自动显示时间的方法、系统和存储介质
JP2017103580A (ja) データ圧縮収集システム、ネットワーク接続装置、データ圧縮収集方法およびプログラム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19764771

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19764771

Country of ref document: EP

Kind code of ref document: A1