CN115436907B - Inversion Method and System for Incoherent Scattering Ionospheric Parameters Based on Bayesian Filtering - Google Patents

Inversion Method and System for Incoherent Scattering Ionospheric Parameters Based on Bayesian Filtering Download PDF

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CN115436907B
CN115436907B CN202211390635.8A CN202211390635A CN115436907B CN 115436907 B CN115436907 B CN 115436907B CN 202211390635 A CN202211390635 A CN 202211390635A CN 115436907 B CN115436907 B CN 115436907B
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郝红连
赵必强
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Institute of Geology and Geophysics of CAS
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Abstract

本发明属于信号与信息处理领域，具体涉及一种基于贝叶斯滤波的非相干散射电离层参量反演方法、系统、装置，旨在解决现有非相干散射雷达的电离层参量提取方法获得的电离层参量分辨率差的问题。本方法包括：获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；得到理论自相关数据；得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；判断是否拟合完成，若否，通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；若是，通过贝叶斯平滑算法进行递归平滑处理，得到最终反演的电离层基本参量。本发明提高了非相干散射电离层参量反演的时间和距离分辨率。

Figure 202211390635

The invention belongs to the field of signal and information processing, and specifically relates to a Bayesian filter-based inversion method, system and device for incoherent scattering ionospheric parameters, aiming at solving the problems obtained by the ionospheric parameter extraction method of the existing incoherent scattering radar The problem of poor resolution of ionospheric parameters. The method comprises: obtaining theoretical initial values and corresponding prior variances of ionospheric basic parameters on all range gates at time k ; obtaining theoretical autocorrelation data; obtaining basic ionospheric parameters fitted on each range gate at time k and corresponding The error covariance matrix of the error covariance matrix; judge whether the fitting is completed, if not, obtain the theoretical initial value and the corresponding prior variance of the basic parameters of the ionosphere on all range gates at time k + 1 through the Bayesian filter method; if so, pass The Bayesian smoothing algorithm performs recursive smoothing to obtain the final inversion of the basic parameters of the ionosphere. The invention improves the time and distance resolution of inversion of incoherent scattering ionosphere parameters.

Figure 202211390635

Description

基于贝叶斯滤波的非相干散射电离层参量反演方法、系统Inversion Method and System for Incoherent Scattering Ionospheric Parameters Based on Bayesian Filtering

技术领域technical field

本发明属于信号与信息处理领域，具体涉及一种基于贝叶斯滤波的非相干散射电离层参量反演方法、系统、装置。The invention belongs to the field of signal and information processing, and in particular relates to a Bayesian filter-based inversion method, system and device for incoherent scattering ionospheric parameters.

背景技术Background technique

对于电离层的非相干散射探测，电离层可以看作是大范围连续分布的软目标，雷达接收到的回波信号是从地面发射的电磁波信号受电离层中的电子、离子的热起伏作用调制后的零均值的后向散射随机信号，回波功率相对于发射功率非常微弱，其功率谱密度是电子密度、电子温度、离子温度、等离子体视线漂移速度等电离层参量的函数。为了从微弱的非相干散射回波信号中提取得到电离层基本参量，大功率的相控阵非相干散射雷达是目前最先进且最有效的探测手段，具有探测范围广、探测电离层参数较多且时间和空间分辨率较高等特点。For the incoherent scattering detection of the ionosphere, the ionosphere can be regarded as a large-scale continuous distribution of soft targets, and the echo signal received by the radar is the electromagnetic wave signal emitted from the ground and modulated by the thermal fluctuation of electrons and ions in the ionosphere For the backscattered random signal with zero mean, the echo power is very weak relative to the transmission power, and its power spectral density is a function of ionospheric parameters such as electron density, electron temperature, ion temperature, and plasma line-of-sight drift velocity. In order to extract the basic parameters of the ionosphere from the weak incoherent scatter echo signals, the high-power phased array incoherent scatter radar is currently the most advanced and effective detection method, with a wide detection range and many ionospheric parameters. And it has the characteristics of high temporal and spatial resolution.

在非相干散射雷达探测中，通常采用长脉冲和交替码作为雷达发射信号。长脉冲回波信号功率相对较高，但是距离分辨率比较差，通常为几十公里，交替码由于其相位编码特性，回波信号功率较低，但是其距离分辨率比较高，通常为几百米到几公里。针对这两种编码形式的回波信号进行电离层参量提取，常规的反演方法是基于距离门分析，即将理论自相关数据与实测非相干散射回波信号的自相关逐个高度进行非线性最小二乘拟合，每个拟合高度使用的理论初值完全依赖于IRI理论模型，不同距离门以及不同时刻之间的拟合都是相互独立的，这样的拟合方法需要准确的非相干散射谱的测量才可以获取较高分辨率的电离层参量，也就是需要高信噪比的非相干散射回波信号。那么为了提高实测回波信号的信噪比，需要先在距离和时间上进行多周期积累后再进行参量反演。一般在相控阵体制的非相干散射雷达多波束扫描探测实验中，为了获取可靠的电离层参量，对于距离分辨率本身比较高的交替码回波信号，进行多个高度积累后，再进行距离门反演得到的电离层参量在十几分钟的时间分辨率和十几公里的距离分辨率量级，长脉冲距离分辨率则变得更差，这对于快速变化的电离层扰动的动力学研究是远远不够的。因此本发明结合时间上的贝叶斯平滑和距离向上的相关先验知识来获取高时间分辨率和高距离分辨率的电离层参量，这对电离层的精细结构研究具有重要的应用价值。In incoherent scattered radar detection, long pulses and alternating codes are usually used as radar transmission signals. The power of the long pulse echo signal is relatively high, but the distance resolution is relatively poor, usually tens of kilometers. Due to its phase encoding characteristics, the echo signal power of the alternating code is relatively low, but its distance resolution is relatively high, usually hundreds of kilometers meters to several kilometers. The ionospheric parameters are extracted from the echo signals of these two encoding forms. The conventional inversion method is based on the range gate analysis, that is, the autocorrelation between the theoretical autocorrelation data and the measured incoherent scattering echo signals is performed height by height by nonlinear least squares. Multiply fitting, the theoretical initial value used for each fitting height is completely dependent on the IRI theoretical model, and the fitting between different range gates and different moments are independent of each other, such a fitting method requires accurate incoherent scattering spectrum The measurement of ionospheric parameters with higher resolution can be obtained, that is, the incoherent scattered echo signal with high signal-to-noise ratio is required. Then, in order to improve the signal-to-noise ratio of the measured echo signal, it is necessary to perform multi-period accumulation in distance and time before performing parameter inversion. Generally, in the multi-beam scanning detection experiment of incoherent scatter radar with phased array system, in order to obtain reliable ionospheric parameters, for the alternating code echo signal with relatively high range resolution itself, after multiple height accumulations, the range The ionospheric parameters obtained by gate inversion are in the order of tens of minutes of time resolution and tens of kilometers of distance resolution, and the long-pulse distance resolution becomes worse. is not enough. Therefore, the present invention combines Bayesian smoothing in time and related prior knowledge of distance upwards to obtain ionospheric parameters with high time resolution and high distance resolution, which has important application value for the fine structure research of ionosphere.

发明内容Contents of the invention

为了解决现有技术中的上述问题，即为了解决现有非相干散射雷达的电离层参量提取方法获得的电离层参量分辨率差的问题，本发明第一方面，提出了一种基于贝叶斯滤波的非相干散射电离层参量反演方法，该方法包括：In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem of poor resolution of the ionospheric parameters obtained by the ionospheric parameter extraction method of the existing incoherent scatter radar, the first aspect of the present invention proposes a method based on Bayesian Filtered incoherent scattering ionospheric parameter inversion method, the method includes:

步骤S100，根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；Step S100, according to the IRI ionospheric model, obtain the theoretical initial values of the basic parameters of the ionosphere on all range gates at time k and their corresponding prior variances; when initializing at time k , it is the actual measurement used in the first fitting The actual moment corresponding to the autocorrelation data; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity;

步骤S200，基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；Step S200, based on the theoretical initial values of the basic parameters of the ionosphere on each range gate at time k , calculate the theoretical spectrum on each range gate through the theoretical model of scattering spectrum, and inverse Fourier transform the theoretical spectrum on each range gate Transform to get theoretical autocorrelation data;

步骤S300，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；Step S300, for each range gate, perform a nonlinear least squares operation on the corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters fitted on each range gate at time k and the corresponding error covariance matrix ;

步骤S400，判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转步骤S600；否则跳转步骤S500；Step S400, judging whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, if so, skip to step S600; otherwise, skip to step S500;

步骤S500，通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转步骤S200；Step S500, obtain the theoretical initial values and the corresponding prior variances of the basic parameters of the ionosphere on all range gates at time k +1 through the Bayesian filtering method, and set k = k +1, and jump to step S200;

步骤S600，通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。In step S600, recursive smoothing is performed on the ionospheric basic parameters and the corresponding error covariance matrix fitted on each range gate at all times within the set time period by Bayesian smoothing algorithm to obtain the final inverted ionospheric basic parameters.

在一些优选的实施方式中，实测自相关数据与理论自相关数据之间的关系为：In some preferred embodiments, the relationship between measured autocorrelation data and theoretical autocorrelation data is:

Figure 860712DEST_PATH_IMAGE001
Figure 860712DEST_PATH_IMAGE001

其中，

Figure 656630DEST_PATH_IMAGE002
、
Figure 675401DEST_PATH_IMAGE003
为雷达接收机实测的原始复信号回波序列，
Figure 291190DEST_PATH_IMAGE004
为时延值，
Figure 53610DEST_PATH_IMAGE005
为由原始信号计算得到的非相干散射回波信号自相关，即实测自相关数据，
Figure 704034DEST_PATH_IMAGE006
为雷达接收机阻抗，
Figure 362549DEST_PATH_IMAGE007
为雷达发射功率，
Figure 996792DEST_PATH_IMAGE008
为发射脉冲宽度，
Figure 31744DEST_PATH_IMAGE009
为从雷达天线到散射点 的距离，
Figure 551324DEST_PATH_IMAGE010
为时延模糊函数，
Figure 911898DEST_PATH_IMAGE011
为距离门
Figure 502279DEST_PATH_IMAGE012
处由电子密度
Figure 340922DEST_PATH_IMAGE013
、电子温度
Figure 231518DEST_PATH_IMAGE014
、 离子温度
Figure 497414DEST_PATH_IMAGE015
、等离子体视线漂移速度
Figure 575091DEST_PATH_IMAGE016
决定的等离子体的理论自相关数据，
Figure 951846DEST_PATH_IMAGE017
为与雷达 天线增益和雷达散射截面等相关的系统常量。 in,
Figure 656630DEST_PATH_IMAGE002
,
Figure 675401DEST_PATH_IMAGE003
is the original complex signal echo sequence measured by the radar receiver,
Figure 291190DEST_PATH_IMAGE004
is the delay value,
Figure 53610DEST_PATH_IMAGE005
is the autocorrelation of the incoherent scattered echo signal calculated from the original signal, that is, the measured autocorrelation data,
Figure 704034DEST_PATH_IMAGE006
is the radar receiver impedance,
Figure 362549DEST_PATH_IMAGE007
is the radar transmit power,
Figure 996792DEST_PATH_IMAGE008
is the emission pulse width,
Figure 31744DEST_PATH_IMAGE009
is the distance from the radar antenna to the scattering point,
Figure 551324DEST_PATH_IMAGE010
is the delay ambiguity function,
Figure 911898DEST_PATH_IMAGE011
is the range gate
Figure 502279DEST_PATH_IMAGE012
electron density
Figure 340922DEST_PATH_IMAGE013
, electron temperature
Figure 231518DEST_PATH_IMAGE014
, ion temperature
Figure 497414DEST_PATH_IMAGE015
, Plasma line-of-sight drift speed
Figure 575091DEST_PATH_IMAGE016
The theoretical autocorrelation data of the determined plasma,
Figure 951846DEST_PATH_IMAGE017
are system constants related to radar antenna gain and radar cross section, etc.

在一些优选的实施方式中，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到各距离门上拟合的电离层基本参量，其方法为：In some preferred embodiments, for each range gate, its corresponding measured autocorrelation data and theoretical autocorrelation data are subjected to nonlinear least squares operation to obtain the ionospheric basic parameters fitted on each range gate, the method is :

根据设定的距离门步进间隔，逐个高度对各距离门对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，进而得到各距离门上拟合的电离层基本参量。According to the set range gate step interval, the measured autocorrelation data corresponding to each range gate and the theoretical autocorrelation data are subjected to nonlinear least squares operation height by altitude, and then the basic parameters of the ionosphere fitted on each range gate are obtained.

在一些优选的实施方式中，在非相干散射雷达探测中，若采用交替码作为雷达发射信号，则将时延剖面矩阵各探测距离上的最小的时延积去掉，不参与实测自相关数据的距离门的拟合。In some preferred embodiments, in the incoherent scattered radar detection, if the alternate code is used as the radar transmission signal, the minimum time delay product at each detection distance of the time delay profile matrix is removed, and does not participate in the integration of the measured autocorrelation data. Fitting of the range gate.

在一些优选的实施方式中，每个距离门处对应的误差协方差矩阵，其获取方法为：In some preferred embodiments, the error covariance matrix corresponding to each range gate is obtained by:

Figure 696948DEST_PATH_IMAGE018
Figure 696948DEST_PATH_IMAGE018

其中，

Figure 133746DEST_PATH_IMAGE019
为误差协方差矩阵，
Figure 964299DEST_PATH_IMAGE020
为拟合残差一阶偏导，
Figure 144744DEST_PATH_IMAGE021
为实测自相关数据的方 差，T表示转置。 in,
Figure 133746DEST_PATH_IMAGE019
is the error covariance matrix,
Figure 964299DEST_PATH_IMAGE020
For the first partial derivative of the fitted residual,
Figure 144744DEST_PATH_IMAGE021
is the variance of the measured autocorrelation data, and T represents the transpose.

在一些优选的实施方式中，通过贝叶斯滤波方法获取k+1时刻所有距离门上的初始基本参量，其方法为：In some preferred embodiments, the initial basic parameters on all range gates at k +1 time are obtained by Bayesian filtering method, and the method is as follows:

若未知的电离层基本参量x的先验值

Figure 744353DEST_PATH_IMAGE022
为真值，电离层基本参量x与其对应的理论 初值的映射关系为
Figure 352052DEST_PATH_IMAGE023
，先验方差为
Figure 404321DEST_PATH_IMAGE024
，则它们之间的线性关系为： If the unknown prior value of the basic ionospheric parameter x
Figure 744353DEST_PATH_IMAGE022
is the true value, the mapping relationship between the basic ionospheric parameter x and its corresponding theoretical initial value is
Figure 352052DEST_PATH_IMAGE023
, the prior variance is
Figure 404321DEST_PATH_IMAGE024
, then the linear relationship between them is:

Figure 388458DEST_PATH_IMAGE025
Figure 388458DEST_PATH_IMAGE025

将

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、
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分别以最大二阶差分形式展开： Will
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,
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Expand respectively in the form of maximum second-order differences:

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，
Figure 680057DEST_PATH_IMAGE027
Figure 160739DEST_PATH_IMAGE026
,
Figure 680057DEST_PATH_IMAGE027

其中，

Figure 988679DEST_PATH_IMAGE028
、
Figure 938180DEST_PATH_IMAGE029
、
Figure 965042DEST_PATH_IMAGE030
分别表示第零阶、第一阶、第二阶的先验方差； in,
Figure 988679DEST_PATH_IMAGE028
,
Figure 938180DEST_PATH_IMAGE029
,
Figure 965042DEST_PATH_IMAGE030
Respectively represent the prior variance of the zeroth order, first order, and second order;

对于每个电离层基本参量，第零阶的差分矩阵为单位矩阵，即

Figure 290981DEST_PATH_IMAGE031
，第一阶 和第二阶差分矩阵
Figure 985268DEST_PATH_IMAGE032
、
Figure 105671DEST_PATH_IMAGE033
分别为
Figure 354249DEST_PATH_IMAGE034
和
Figure 218300DEST_PATH_IMAGE035
的矩阵形式，表示为： For each basic ionospheric parameter, the difference matrix of the zeroth order is the identity matrix, namely
Figure 290981DEST_PATH_IMAGE031
, the first-order and second-order difference matrices
Figure 985268DEST_PATH_IMAGE032
,
Figure 105671DEST_PATH_IMAGE033
respectively
Figure 354249DEST_PATH_IMAGE034
and
Figure 218300DEST_PATH_IMAGE035
In matrix form, expressed as:

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，
Figure 58397DEST_PATH_IMAGE037
Figure 767093DEST_PATH_IMAGE036
,
Figure 58397DEST_PATH_IMAGE037

其中，

Figure 794272DEST_PATH_IMAGE038
表示距离门个数； in,
Figure 794272DEST_PATH_IMAGE038
Indicates the number of range gates;

前一时刻拟合获得的所有距离门上的误差协方差矩阵可以作为第零阶协方差矩阵，由此可以进一步推导得到第一阶和第二阶协方差矩阵，分别为The error covariance matrix on all range gates obtained by fitting at the previous moment can be used as the zeroth-order covariance matrix, and the first-order and second-order covariance matrices can be further derived, respectively,

Figure 196434DEST_PATH_IMAGE039
Figure 196434DEST_PATH_IMAGE039

其中，

Figure 599734DEST_PATH_IMAGE040
为取对角线，
Figure 61939DEST_PATH_IMAGE041
为距离门步进间隔，
Figure 550690DEST_PATH_IMAGE042
为每个参数的相关长 度，正比于等离子体标高
Figure 22122DEST_PATH_IMAGE043
，
Figure 14349DEST_PATH_IMAGE044
为常量，
Figure 650385DEST_PATH_IMAGE045
表示k时刻第
Figure 626432DEST_PATH_IMAGE046
个距离门的协方差矩阵； in,
Figure 599734DEST_PATH_IMAGE040
To take the diagonal,
Figure 61939DEST_PATH_IMAGE041
is the stepping interval of the range gate,
Figure 550690DEST_PATH_IMAGE042
is the correlation length for each parameter, proportional to the plasma elevation
Figure 22122DEST_PATH_IMAGE043
,
Figure 14349DEST_PATH_IMAGE044
as a constant,
Figure 650385DEST_PATH_IMAGE045
Indicates that the kth time
Figure 626432DEST_PATH_IMAGE046
covariance matrix of range gates;

运用最小二乘思想计算

Figure 635976DEST_PATH_IMAGE047
达到最小，那么从上述的线性 关系的公式可得到： Using the least squares thinking to calculate
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Reaching the minimum, then from the above linear relationship formula can be obtained:

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Figure 748288DEST_PATH_IMAGE048

其中，

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为贝叶斯滤波后的参数剖面，
Figure 750059DEST_PATH_IMAGE050
为贝叶斯滤波后的协方差矩阵，T表示转 置；因此基于贝叶斯滤波后下一时刻电离层基本参量的理论初值
Figure 828874DEST_PATH_IMAGE051
和对应的先验方差
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分别为 in,
Figure 817876DEST_PATH_IMAGE049
is the parameter profile after Bayesian filtering,
Figure 750059DEST_PATH_IMAGE050
is the covariance matrix after Bayesian filtering, and T represents the transpose; therefore, based on the theoretical initial value of the basic parameters of the ionosphere at the next moment after Bayesian filtering
Figure 828874DEST_PATH_IMAGE051
and the corresponding prior variance
Figure 530114DEST_PATH_IMAGE052
respectively

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Figure 36181DEST_PATH_IMAGE053

其中，

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为时间步进间隔，即拟合过程中的积累时间，
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为常量，
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为过程噪声 方差。 in,
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is the time step interval, that is, the accumulation time in the fitting process,
Figure 807008DEST_PATH_IMAGE055
as a constant,
Figure 628334DEST_PATH_IMAGE056
is the process noise variance.

本发明的第二方面，提出了一种基于贝叶斯滤波的非相干散射电离层参量反演系统，该系统包括：参量初值获取模块、理论自相关计算模块、参量输出模块、循环判断模块、贝叶斯滤波模块、贝叶斯平滑模块；In the second aspect of the present invention, a Bayesian filter-based incoherent scattering ionospheric parameter inversion system is proposed, the system includes: a parameter initial value acquisition module, a theoretical autocorrelation calculation module, a parameter output module, and a loop judgment module , Bayesian filtering module, Bayesian smoothing module;

所述参量初值获取模块，配置为根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；The parameter initial value acquisition module is configured to obtain theoretical initial values and corresponding prior variances of the ionospheric basic parameters on all range gates at time k according to the IRI ionospheric model; The actual moment corresponding to the measured autocorrelation data used during fitting; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity;

所述理论自相关计算模块，配置为基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；The theoretical autocorrelation calculation module is configured to calculate the theoretical spectrum on each range gate based on the theoretical initial value of the ionospheric basic parameters on each range gate at time k , and calculate the theoretical spectrum on each range gate through the scattering spectrum theoretical model, and calculate the theoretical spectrum on each range gate. Inverse Fourier transform is performed on the theoretical spectrum to obtain theoretical autocorrelation data;

所述参量输出模块，配置为对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；The parameter output module is configured to perform a nonlinear least squares operation on each range gate with its corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters and corresponding The error covariance matrix of ;

所述循环判断模块，配置为判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转所述贝叶斯平滑模块；否则跳转所述贝叶斯滤波模块；The loop judgment module is configured to judge whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, and if so, jump to the Bayesian smoothing module; Otherwise, jump to the Bayesian filtering module;

所述贝叶斯滤波模块，配置为通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转所述理论自相关计算；The Bayesian filtering module is configured to obtain theoretical initial values and corresponding prior variances of the ionospheric basic parameters on all range gates at k +1 moment by Bayesian filtering method, and make k = k +1, Jump to the theoretical autocorrelation calculation;

所述贝叶斯平滑模块，配置为通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。The Bayesian smoothing module is configured to recursively smooth the basic parameters of the ionosphere and the corresponding error covariance matrix fitted on each range gate at all times within the set time period through the Bayesian smoothing algorithm to obtain the final response The basic parameters of the ionosphere.

本发明的第三方面，提出了一种存储装置，其中存储有多条程序，所述程序应用由处理器加载并执行以实现上述的基于贝叶斯滤波的非相干散射电离层参量反演方法。In the third aspect of the present invention, a storage device is proposed, wherein a plurality of programs are stored, and the program application is loaded and executed by a processor to realize the above-mentioned incoherent scattering ionospheric parameter inversion method based on Bayesian filtering .

本发明的第四方面，提出了一种处理装置，包括处理器、存储装置；处理器，适用于执行各条程序；存储装置，适用于存储多条程序；所述程序适用于由处理器加载并执行以实现上述的基于贝叶斯滤波的非相干散射电离层参量反演方法。In the fourth aspect of the present invention, a processing device is proposed, including a processor and a storage device; the processor is suitable for executing various programs; the storage device is suitable for storing multiple programs; the program is suitable for being loaded by the processor And execute to realize the above-mentioned Bayesian filtering-based incoherent scattering ionospheric parameter inversion method.

本发明的有益效果：Beneficial effects of the present invention:

本发明提高了非相干散射电离层参量反演的时间和距离分辨率。The invention improves the time and distance resolution of inversion of incoherent scattering ionosphere parameters.

本发明结合电离层参量反演中前一时刻拟合得到的参量和其误差协方差，基于贝叶斯滤波方法来进行下一时刻距离门拟合的理论初值和先验方差的预测，并利用不同高度之间先验信息的相关性来控制等离子体参数在时间和空间上的梯度，从而获得高分辨率的电离层参量。The present invention combines the parameters and the error covariance obtained by fitting at the previous moment in the ionospheric parameter inversion, based on the Bayesian filtering method to predict the theoretical initial value and prior variance of the range gate fitting at the next moment, and The correlation of prior information between different altitudes is used to control the gradient of plasma parameters in time and space, so as to obtain high-resolution ionospheric parameters.

附图说明Description of drawings

通过阅读参照以下附图所做的对非限制性实施例所做的详细描述，本申请的其他特征、目的和优点将会变得更明显。Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings.

图1是本发明一种实施例的基于贝叶斯滤波的非相干散射电离层参量反演方法的流程示意图；Fig. 1 is a schematic flow chart of an incoherent scattering ionospheric parameter inversion method based on Bayesian filtering in an embodiment of the present invention;

图2是本发明一种实施例的实测非相干散射回波信号自相关数据的距离门形成示意图；Fig. 2 is a schematic diagram of range gate formation of measured incoherent scattered echo signal autocorrelation data according to an embodiment of the present invention;

图3是本发明一种实施例的基于贝叶斯滤波的非相干散射电离层参量反演系统的框架示意图；Fig. 3 is a schematic frame diagram of an incoherent scattering ionospheric parameter inversion system based on Bayesian filtering according to an embodiment of the present invention;

图4是本发明一种实施例的交替码回波信号的电离层参量反演结果的示意图；Fig. 4 is a schematic diagram of an ionospheric parameter inversion result of an alternate code echo signal according to an embodiment of the present invention;

图5是本发明一种实施例的长脉冲回波信号的电离层参量反演结果的示意图；Fig. 5 is a schematic diagram of an ionospheric parameter inversion result of a long pulse echo signal according to an embodiment of the present invention;

图6是本发明一种实施例的适于用来实现本申请实施例的电子设备的计算机系统的结构示意图。FIG. 6 is a schematic structural diagram of a computer system suitable for realizing the electronic device of the embodiment of the present application according to an embodiment of the present invention.

具体实施方式Detailed ways

为使本发明的目的、技术方案和优点更加清楚，下面将结合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。In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than Full examples. 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.

下面结合附图和实施例对本申请作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅用于解释相关发明，而非对该发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, not to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

本发明的基于贝叶斯滤波的非相干散射电离层参量反演方法，如图1所示，包括以下步骤：The incoherent scattering ionospheric parameter inversion method based on Bayesian filter of the present invention, as shown in Figure 1, comprises the following steps:

步骤S100，根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；Step S100, according to the IRI ionospheric model, obtain the theoretical initial values of the basic parameters of the ionosphere on all range gates at time k and their corresponding prior variances; when initializing at time k , it is the actual measurement used in the first fitting The actual moment corresponding to the autocorrelation data; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity;

步骤S200，基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；Step S200, based on the theoretical initial values of the basic parameters of the ionosphere on each range gate at time k , calculate the theoretical spectrum on each range gate through the theoretical model of scattering spectrum, and inverse Fourier transform the theoretical spectrum on each range gate Transform to get theoretical autocorrelation data;

步骤S300，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；Step S300, for each range gate, perform a nonlinear least squares operation on the corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters fitted on each range gate at time k and the corresponding error covariance matrix ;

步骤S400，判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转步骤S600；否则跳转步骤S500；Step S400, judging whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, if so, skip to step S600; otherwise, skip to step S500;

步骤S500，通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转步骤S200；Step S500, obtain the theoretical initial values and the corresponding prior variances of the basic parameters of the ionosphere on all range gates at time k +1 through the Bayesian filtering method, and set k = k +1, and jump to step S200;

步骤S600，通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。In step S600, recursive smoothing is performed on the ionospheric basic parameters and the corresponding error covariance matrix fitted on each range gate at all times within the set time period by Bayesian smoothing algorithm to obtain the final inverted ionospheric basic parameters.

为了更清晰地对本发明基于贝叶斯滤波的非相干散射电离层参量反演方法进行说明，下面结合附图对本发明方法一种实施例中各步骤进行展开详述。In order to describe the Bayesian filtering-based incoherent scattering ionospheric parameter retrieval method of the present invention more clearly, each step in an embodiment of the method of the present invention will be described in detail below in conjunction with the accompanying drawings.

步骤S100，根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；Step S100, according to the IRI ionospheric model, obtain the theoretical initial values of the basic parameters of the ionosphere on all range gates at time k and their corresponding prior variances; when initializing at time k , it is the actual measurement used in the first fitting The actual moment corresponding to the autocorrelation data; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity;

在本实施例中，从IRI电离层模型获取第一时刻所有距离门上的四个待测的电离 层基本参量即电子密度

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、电子温度
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、离子温度
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、等离子体视线漂移速度
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，作为理 论谱计算的参量初值，同时也获取其对应的先验方差，用于拟合过程中的加权系数。其中， 第一时刻，即k时刻，初始化时为在第一次拟合时所采用的实测自相关数据对应的实际时 刻。 In this embodiment, the four ionospheric basic parameters to be measured on all range gates at the first moment are obtained from the IRI ionospheric model, that is, the electron density
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, electron temperature
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, ion temperature
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, Plasma line-of-sight drift speed
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, as the initial value of the parameter for theoretical spectrum calculation, and its corresponding prior variance is also obtained, which is used as the weighting coefficient in the fitting process. Wherein, the first moment, that is, the k moment, is the actual moment corresponding to the measured autocorrelation data used in the first fitting at the time of initialization.

步骤S200，基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；Step S200, based on the theoretical initial values of the basic parameters of the ionosphere on each range gate at time k , calculate the theoretical spectrum on each range gate through the theoretical model of scattering spectrum, and inverse Fourier transform the theoretical spectrum on each range gate Transform to get theoretical autocorrelation data;

在本实施例中，将电离层基本参量的理论初值作为散射谱理论模型的初始输入，并计算每个距离门上的理论谱。功率谱与自相关之间互为傅里叶变换对，理论谱进一步通过逆傅里叶变换得到理论自相关数据。In this embodiment, the theoretical initial values of the basic parameters of the ionosphere are used as the initial input of the theoretical model of the scattering spectrum, and the theoretical spectrum on each range gate is calculated. The power spectrum and autocorrelation are a Fourier transform pair, and the theoretical spectrum is further obtained by inverse Fourier transform to obtain theoretical autocorrelation data.

步骤S300，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；Step S300, for each range gate, perform a nonlinear least squares operation on the corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters fitted on each range gate at time k and the corresponding error covariance matrix ;

在本实施例中，实测自相关数据的距离门形成如图2所示，以本发明为例，假设时 延剖面矩阵包含八个探测距离，每个探测距离上有四个时延积如

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、
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、
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、
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，每个时延积处根据设置的距离门求和法则进行数据重组，如每三个探测距离上的 时延积组成一个距离门上的自相关数据，即对于
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将时延剖面矩阵中
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、
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、
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处的
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数据重新排列形成距离门0的
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数据，
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、
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、
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处的
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数据重新排列形成 距离门1的
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数据，依此类推完成预设所有距离门的时延积重组。特别对于交替码，由于
Figure 596847DEST_PATH_IMAGE059
处具有较大的距离模糊，所以需要把
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处的时延积去掉，不参与距离门的拟合。 In this embodiment, the range gate formation of the measured autocorrelation data is shown in Figure 2. Taking the present invention as an example, it is assumed that the delay profile matrix includes eight detection distances, and each detection distance has four delay products such as
Figure 890819DEST_PATH_IMAGE059
,
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,
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,
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, each time-delay product is reorganized according to the set range gate summation rule, for example, the time-delay products on every three detection distances form an autocorrelation data on the range gate, that is, for
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Into the delay profile matrix
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,
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,
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of
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The data is rearranged to form a range gate of 0
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data,
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,
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,
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of
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The data is rearranged to form a range gate of 1
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Data, and so on to complete the delay product reorganization of all preset range gates. Especially for alternate codes, since
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has a large distance blur, so it is necessary to put
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The time delay product at is removed and does not participate in the fitting of the range gate.

理论自相关和实测非相干散射回波信号的自相关之间的关系表示为：The relationship between the theoretical autocorrelation and the measured autocorrelation of the incoherent scattered echo signal is expressed as:

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（1）
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(1)

其中，

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、
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为雷达接收机实测的原始复信号回波序列，
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为时延值， 是采样间隔的整数倍，
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为由原始信号计算得到的非相干散射回波信号自相关， 即实测自相关数据，
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为雷达接收机阻抗，
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为雷达发射功率（W），
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为发射脉冲宽度（s），
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为从雷达天线到散射点的距离（m），
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为时延模糊函数，
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为距离门
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处由电子密度
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、电子温度
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、离子温度
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、等离子体视线漂移速度
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决定的等离子体理 论自相关数据，
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为与雷达天线增益和雷达散射截面等相关的系统常量（
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）。 in,
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,
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is the original complex signal echo sequence measured by the radar receiver,
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is the delay value, is an integer multiple of the sampling interval,
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is the autocorrelation of the incoherent scattered echo signal calculated from the original signal, that is, the measured autocorrelation data,
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is the radar receiver impedance,
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is the radar transmit power (W),
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is the emission pulse width (s),
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is the distance from the radar antenna to the scattering point (m),
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is the delay ambiguity function,
Figure 464693DEST_PATH_IMAGE074
is the range gate
Figure 243293DEST_PATH_IMAGE075
electron density
Figure 48438DEST_PATH_IMAGE013
, electron temperature
Figure 305107DEST_PATH_IMAGE014
, ion temperature
Figure 879308DEST_PATH_IMAGE015
, Plasma line-of-sight drift speed
Figure 828809DEST_PATH_IMAGE016
Determined by the theoretical autocorrelation data of the plasma,
Figure 121250DEST_PATH_IMAGE017
is the system constant related to radar antenna gain and radar cross section (
Figure 181610DEST_PATH_IMAGE076
).

然后通过Levenberg-Marquardt 非线性最小二乘算法，不断调整理论谱的输入值，使得理论自相关与实测自相关的残差平方和达到最小则停止迭代计算，从而得到最终可信的四个电离层基本参量，包括电子密度、电子温度、离子温度和等离子体视线漂移速度。同时可以得到每个距离门对应的误差协方差矩阵为4×4的矩阵：Then, through the Levenberg-Marquardt nonlinear least squares algorithm, the input value of the theoretical spectrum is continuously adjusted, so that the residual sum of squares of the theoretical autocorrelation and the measured autocorrelation reaches the minimum, and then the iterative calculation is stopped, so as to obtain the final credible four ionosphere Basic parameters, including electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity. At the same time, the error covariance matrix corresponding to each range gate can be obtained as a 4×4 matrix:

Figure 344738DEST_PATH_IMAGE018
（2）
Figure 344738DEST_PATH_IMAGE018
(2)

其中，

Figure 730720DEST_PATH_IMAGE077
为误差协方差矩阵，
Figure 244878DEST_PATH_IMAGE020
为拟合残差一阶偏导，
Figure 108929DEST_PATH_IMAGE078
为实测自相关数据的方 差，T表示转置。 in,
Figure 730720DEST_PATH_IMAGE077
is the error covariance matrix,
Figure 244878DEST_PATH_IMAGE020
For the first partial derivative of the fitted residual,
Figure 108929DEST_PATH_IMAGE078
is the variance of the measured autocorrelation data, and T represents the transpose.

即根据设定的距离门步进间隔，逐个高度对各距离门对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，进而得到各距离门上拟合的电离层基本参量。That is, according to the set range gate step interval, the measured autocorrelation data corresponding to each range gate and the theoretical autocorrelation data are subjected to nonlinear least squares operation height by height, and then the basic parameters of the ionosphere fitted on each range gate are obtained.

所有距离门上的四个电离层基本参量矩阵形式为：The matrix form of the four basic ionospheric parameters on all range gates is:

Figure 657722DEST_PATH_IMAGE079
（3）
Figure 657722DEST_PATH_IMAGE079
(3)

其中，

Figure 949026DEST_PATH_IMAGE038
为距离门个数，
Figure 950480DEST_PATH_IMAGE080
、
Figure 615292DEST_PATH_IMAGE081
、
Figure 18592DEST_PATH_IMAGE082
、
Figure 480797DEST_PATH_IMAGE083
分别为反演得到的k时刻
Figure 438389DEST_PATH_IMAGE046
个距离门的电 子密度、电子温度、离子温度和等离子体视线漂移速度矩阵，误差协方差矩阵也用类似的矩 阵形式定义。 in,
Figure 949026DEST_PATH_IMAGE038
is the number of distance gates,
Figure 950480DEST_PATH_IMAGE080
,
Figure 615292DEST_PATH_IMAGE081
,
Figure 18592DEST_PATH_IMAGE082
,
Figure 480797DEST_PATH_IMAGE083
are the time k obtained by inversion
Figure 438389DEST_PATH_IMAGE046
The electron density, electron temperature, ion temperature, and plasma line-of-sight drift velocity matrices of a range gate, and the error covariance matrix are also defined in a similar matrix form.

步骤S400，判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转步骤S600；否则跳转步骤S500；Step S400, judging whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, if so, skip to step S600; otherwise, skip to step S500;

在本实施例中，对设定时间段内所有时刻进行拟合，得到所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若没有拟合完成，则跳转步骤S500；否则，跳转步骤S600，对拟合的所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵进行进一步处理。In this embodiment, fitting is performed on all moments within the set time period to obtain the basic parameters of the ionosphere on each range gate at all moments and the corresponding error covariance matrix. If the fitting is not completed, skip to step S500; Otherwise, jump to step S600 to further process the fitted ionospheric basic parameters and corresponding error covariance matrix on each range gate at all times.

步骤S500，通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转步骤S200；Step S500, obtain the theoretical initial values and the corresponding prior variances of the basic parameters of the ionosphere on all range gates at time k +1 through the Bayesian filtering method, and set k = k +1, and jump to step S200;

在本实施例中，假设前一时刻获得的所有距离门上的四个电离层基本参量矢量和误差协方差矩阵表示为：In this embodiment, it is assumed that the four ionospheric basic parameter vectors and the error covariance matrix on all range gates obtained at the previous moment are expressed as:

Figure 909821DEST_PATH_IMAGE084
（4）
Figure 909821DEST_PATH_IMAGE084
(4)

结合相关先验理论，用前一时刻获得的电离层参量和协方差矩阵作为先验知识来 构建下一时刻拟合需要的参量剖面初值。假设未知的电离层基本参量x的先验值

Figure 902048DEST_PATH_IMAGE022
为真值， 获取参量x的理论初值的问题可以看作是线性反演问题，线性映射关系为
Figure 66313DEST_PATH_IMAGE085
，先验方差为
Figure 776780DEST_PATH_IMAGE086
，那么可以表示为如下线性关系： Combined with relevant prior theory, the ionospheric parameters and covariance matrix obtained at the previous moment are used as prior knowledge to construct the initial value of the parameter profile required for fitting at the next moment. Assuming an unknown prior value of the ionospheric fundamental parameter x
Figure 902048DEST_PATH_IMAGE022
is the true value, the problem of obtaining the theoretical initial value of the parameter x can be regarded as a linear inversion problem, and the linear mapping relationship is
Figure 66313DEST_PATH_IMAGE085
, the prior variance is
Figure 776780DEST_PATH_IMAGE086
, then it can be expressed as the following linear relationship:

Figure 520745DEST_PATH_IMAGE087
（5）
Figure 520745DEST_PATH_IMAGE087
(5)

上式（5）中的

Figure 633058DEST_PATH_IMAGE022
可以用前一时刻拟合得到的参数矢量
Figure 702645DEST_PATH_IMAGE088
和协方差矩阵
Figure 900408DEST_PATH_IMAGE089
代替。同 时引入与差分先验具有类似平滑属性的先验分布,即使用前一时刻获得的所有距离门上的 参量值进行加权从而达到距离门上的平滑。另外
Figure 713643DEST_PATH_IMAGE085
、
Figure 680462DEST_PATH_IMAGE024
分别以最大二阶差分形式展开为如 下： In the above formula (5)
Figure 633058DEST_PATH_IMAGE022
The parameter vector obtained by fitting at the previous moment can be used
Figure 702645DEST_PATH_IMAGE088
and covariance matrix
Figure 900408DEST_PATH_IMAGE089
replace. At the same time, a priori distribution with similar smoothness properties to the difference priori is introduced, that is, all the parameter values on the range gate obtained at the previous moment are used to weight to achieve smoothness on the range gate. in addition
Figure 713643DEST_PATH_IMAGE085
,
Figure 680462DEST_PATH_IMAGE024
Respectively expanded in the form of the maximum second-order difference as follows:

Figure 920951DEST_PATH_IMAGE026
，
Figure 340431DEST_PATH_IMAGE090
（6）
Figure 920951DEST_PATH_IMAGE026
,
Figure 340431DEST_PATH_IMAGE090
(6)

其中，

Figure 957357DEST_PATH_IMAGE091
、
Figure 778682DEST_PATH_IMAGE092
、
Figure 190072DEST_PATH_IMAGE030
分别表示第零阶、第一阶、第二阶的先验方差。 in,
Figure 957357DEST_PATH_IMAGE091
,
Figure 778682DEST_PATH_IMAGE092
,
Figure 190072DEST_PATH_IMAGE030
Represent the prior variance of the zeroth order, first order, and second order, respectively.

对于每个电离层参量，第零阶的差分矩阵为单位矩阵，即

Figure 99778DEST_PATH_IMAGE031
，第一阶和第 二阶差分矩阵
Figure 254816DEST_PATH_IMAGE093
、
Figure 196227DEST_PATH_IMAGE033
分别为
Figure 44097DEST_PATH_IMAGE094
和
Figure 438170DEST_PATH_IMAGE035
的矩阵形式，表示为： For each ionospheric parameter, the difference matrix of the zeroth order is the identity matrix, namely
Figure 99778DEST_PATH_IMAGE031
, the first-order and second-order difference matrices
Figure 254816DEST_PATH_IMAGE093
,
Figure 196227DEST_PATH_IMAGE033
respectively
Figure 44097DEST_PATH_IMAGE094
and
Figure 438170DEST_PATH_IMAGE035
In matrix form, expressed as:

Figure 131319DEST_PATH_IMAGE095
，
Figure 927237DEST_PATH_IMAGE096
（7）
Figure 131319DEST_PATH_IMAGE095
,
Figure 927237DEST_PATH_IMAGE096
(7)

前一时刻拟合获得的所有距离门上的误差协方差矩阵可以作为第零阶协方差矩阵，由此可以进一步推导得到第一阶和第二阶协方差矩阵，分别为：The error covariance matrix on all range gates obtained by fitting at the previous moment can be used as the zeroth-order covariance matrix, from which the first-order and second-order covariance matrices can be further derived, respectively:

Figure 680429DEST_PATH_IMAGE097
（8）
Figure 680429DEST_PATH_IMAGE097
(8)

其中，

Figure 561797DEST_PATH_IMAGE098
为取对角线，
Figure 324217DEST_PATH_IMAGE041
为距离门步进间隔，
Figure 974641DEST_PATH_IMAGE099
为每个参数的相关长 度，正比于等离子体标高
Figure 633156DEST_PATH_IMAGE100
，
Figure 267399DEST_PATH_IMAGE044
为常量，通过调整
Figure 302351DEST_PATH_IMAGE044
来保持参数剖面在距离上的有效平滑。 对于不同的电离层参量，如电子密度、电子温度、离子温度和等离子体视线漂移速度，
Figure 72861DEST_PATH_IMAGE044
设 置不同。 in,
Figure 561797DEST_PATH_IMAGE098
To take the diagonal,
Figure 324217DEST_PATH_IMAGE041
is the stepping interval of the range gate,
Figure 974641DEST_PATH_IMAGE099
is the correlation length for each parameter, proportional to the plasma elevation
Figure 633156DEST_PATH_IMAGE100
,
Figure 267399DEST_PATH_IMAGE044
as a constant, by adjusting
Figure 302351DEST_PATH_IMAGE044
to keep the parametric profile effectively smooth over distance. For different ionospheric parameters such as electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity,
Figure 72861DEST_PATH_IMAGE044
The settings are different.

运用最小二乘思想计算

Figure 902277DEST_PATH_IMAGE101
达到最小，那么从等式（5）可得 到： Using the least squares thinking to calculate
Figure 902277DEST_PATH_IMAGE101
reaches the minimum, then from equation (5):

Figure 758238DEST_PATH_IMAGE102
（9）
Figure 758238DEST_PATH_IMAGE102
(9)

其中，

Figure 862460DEST_PATH_IMAGE103
为贝叶斯滤波后的参数剖面，
Figure 221897DEST_PATH_IMAGE104
为贝叶斯滤波后的协方差矩阵，T表示转 置；因此基于贝叶斯滤波后下一时刻电离层参量理论初值
Figure 484864DEST_PATH_IMAGE105
和对应的先验方差
Figure 562541DEST_PATH_IMAGE106
分 别为： in,
Figure 862460DEST_PATH_IMAGE103
is the parameter profile after Bayesian filtering,
Figure 221897DEST_PATH_IMAGE104
is the covariance matrix after Bayesian filtering, and T represents the transpose; therefore, based on the theoretical initial value of the ionospheric parameters at the next moment after Bayesian filtering
Figure 484864DEST_PATH_IMAGE105
and the corresponding prior variance
Figure 562541DEST_PATH_IMAGE106
They are:

Figure 204875DEST_PATH_IMAGE053
（10）
Figure 204875DEST_PATH_IMAGE053
(10)

这里，

Figure 949977DEST_PATH_IMAGE054
为时间步进间隔，即拟合过程中的积累时间，
Figure 386775DEST_PATH_IMAGE055
为常量，
Figure 951748DEST_PATH_IMAGE107
为过程噪 声方差，即通过调整
Figure 132194DEST_PATH_IMAGE055
来控制过程噪声方差，使得从一个时刻到另一个时刻引入的部分相关 先验信息保持时间上的相关性。当然，对于不同的电离层参量，
Figure 731802DEST_PATH_IMAGE055
设置也不同。 here,
Figure 949977DEST_PATH_IMAGE054
is the time step interval, that is, the accumulation time in the fitting process,
Figure 386775DEST_PATH_IMAGE055
as a constant,
Figure 951748DEST_PATH_IMAGE107
is the process noise variance, that is, by adjusting
Figure 132194DEST_PATH_IMAGE055
to control the process noise variance so that the partially relevant prior information introduced from one moment to another remains temporally correlated. Of course, for different ionospheric parameters,
Figure 731802DEST_PATH_IMAGE055
The settings are also different.

步骤S600，通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。In step S600, recursive smoothing is performed on the ionospheric basic parameters and the corresponding error covariance matrix fitted on each range gate at all times within the set time period by Bayesian smoothing algorithm to obtain the final inverted ionospheric basic parameters.

在本实施例中，当积累时间足够短时，等离子体参数在前一时刻和当前时刻之间变化很小，利用Rauch-Rung-Striebel（RTS）贝叶斯平滑算法对全部拟合完毕的数据进行进一步的平滑处理得到最终高分辨率的电离层参量，其运用RTS的后向递推方程如下：In this embodiment, when the accumulation time is short enough, the plasma parameters change little between the previous moment and the current moment, and the Rauch-Rung-Striebel (RTS) Bayesian smoothing algorithm is used to smooth all the fitted data Further smoothing is performed to obtain the final high-resolution ionospheric parameters, and the backward recurrence equation using RTS is as follows:

Figure 605080DEST_PATH_IMAGE108
（11）
Figure 605080DEST_PATH_IMAGE108
(11)

这里

Figure 657350DEST_PATH_IMAGE109
和
Figure 375907DEST_PATH_IMAGE110
分别为k时刻的拟合参量结果和对应的误差协方差矩阵，
Figure 830023DEST_PATH_IMAGE111
和
Figure 874202DEST_PATH_IMAGE112
分别为贝叶斯滤波后预测的k+1时刻的理论初值和先验协方差矩阵，
Figure 413768DEST_PATH_IMAGE113
和
Figure 201595DEST_PATH_IMAGE114
为贝叶 斯平滑后k时刻的参量结果和误差协方差矩阵，
Figure 510217DEST_PATH_IMAGE115
和
Figure 725297DEST_PATH_IMAGE116
为贝叶斯平滑后k+1时刻的参 量结果和误差协方差矩阵，
Figure 486580DEST_PATH_IMAGE117
为k时刻的动态预测模型矩阵。即通过贝叶斯平滑算法将相邻 时刻的电离层基本参量以及对应的误差协方差矩阵进行递推平滑处理，进而得到各时刻最 终反演的电离层基本参量。 here
Figure 657350DEST_PATH_IMAGE109
and
Figure 375907DEST_PATH_IMAGE110
Respectively, the fitting parameter results at time k and the corresponding error covariance matrix,
Figure 830023DEST_PATH_IMAGE111
and
Figure 874202DEST_PATH_IMAGE112
are the theoretical initial value and prior covariance matrix predicted at time k+1 after Bayesian filtering, respectively,
Figure 413768DEST_PATH_IMAGE113
and
Figure 201595DEST_PATH_IMAGE114
is the parameter result and error covariance matrix at time k after Bayesian smoothing,
Figure 510217DEST_PATH_IMAGE115
and
Figure 725297DEST_PATH_IMAGE116
is the parameter result and error covariance matrix at time k+1 after Bayesian smoothing,
Figure 486580DEST_PATH_IMAGE117
is the dynamic prediction model matrix at time k. That is, the basic parameters of the ionosphere at adjacent times and the corresponding error covariance matrix are recursively smoothed through the Bayesian smoothing algorithm, and then the basic parameters of the ionosphere that are finally inverted at each time are obtained.

为了证明本发明反演方法的有效性，通过三亚非相干散射雷达的2021年4月14日的交替码和长脉冲几乎同时探测的实测数据进行验证。其中交替码参数为16位交替码，三分之一分数阶采样，码元宽度30us，采样间隔10us；长脉冲参数为脉冲宽度480us，采样间隔10us。In order to prove the effectiveness of the inversion method of the present invention, it is verified by the almost simultaneous detection data of the alternating code and the long pulse of the Sanya incoherent scattering radar on April 14, 2021. Among them, the alternate code parameter is 16-bit alternate code, one-third fractional sampling, symbol width 30us, sampling interval 10us; long pulse parameter is pulse width 480us, sampling interval 10us.

如图4所示为交替码回波信号反演得到的电子密度、电子温度、离子温度和等离子体视线漂移速度的电离层参量，时间分辨率为12s，距离分辨率为4.5km。As shown in Figure 4, the ionospheric parameters of electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity obtained from the inversion of alternating code echo signals, the time resolution is 12s, and the distance resolution is 4.5km.

如图5所示为长脉冲回波信号反演得到的电子密度、电子温度、离子温度和等离子体视线漂移速度的电离层参量，时间分辨率为18s，距离分辨率200km以下为9km、200-400km为18km，400km以上为24km。As shown in Figure 5, the ionospheric parameters of electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity obtained from long pulse echo signal inversion, the time resolution is 18s, and the distance resolution is 9km, 200- 18km for 400km and 24km for more than 400km.

由图4和图5可以看出，在两种编码方式下反演得到的电离层参量剖面均具有较高的时间分辨率，交替码虽然回波信号很微弱，反演后仍然可以得到较高的距离分辨率，说明了本发明用于非相干散射雷达进行探测可以大大提高非相干散射电离层参量反演的时间和距离分辨率。It can be seen from Fig. 4 and Fig. 5 that the ionospheric parameter profiles obtained by the inversion under the two coding methods all have relatively high time resolution. Although the echo signal of the alternating code is very weak, a high The distance resolution shows that the invention can greatly improve the time and distance resolution of incoherent scattering ionospheric parameter inversion when the invention is used for incoherent scattering radar detection.

本发明第二实施例的一种基于贝叶斯滤波的非相干散射电离层参量反演系统，如图3所示，包括：参量初值获取模块100、理论自相关计算模块200、参量输出模块300、循环判断模块400、贝叶斯滤波模块500、贝叶斯平滑模块600；An incoherent scattering ionospheric parameter inversion system based on Bayesian filtering in the second embodiment of the present invention, as shown in FIG. 3 , includes: a parameter initial value acquisition module 100, a theoretical autocorrelation calculation module 200, and a parameter output module 300, loop judgment module 400, Bayesian filtering module 500, Bayesian smoothing module 600;

所述参量初值获取模块100，配置为根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；The parameter initial value acquisition module 100 is configured to obtain theoretical initial values and corresponding prior variances of the ionospheric basic parameters on all range gates at time k according to the IRI ionospheric model; The actual moment corresponding to the measured autocorrelation data adopted during the second fitting; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity;

所述理论自相关计算模块200，配置为基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；The theoretical autocorrelation calculation module 200 is configured to calculate the theoretical spectrum on each range gate through the theoretical model of scattering spectrum based on the theoretical initial value of the ionospheric basic parameters on each range gate at time k , and calculate the theoretical spectrum on each range gate. Inverse Fourier transform of the theoretical spectrum to obtain theoretical autocorrelation data;

所述参量输出模块300，配置为对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；The parameter output module 300 is configured to perform a non-linear least squares operation on each range gate with its corresponding measured autocorrelation data and theoretical autocorrelation data, to obtain the ionospheric basic parameters and The corresponding error covariance matrix;

所述循环判断模块400，配置为判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转所述贝叶斯平滑模块600；否则跳转所述贝叶斯滤波模块500；The loop judgment module 400 is configured to judge whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, and if so, jump to the Bayesian smoothing module 600; otherwise, jump to the Bayesian filtering module 500;

所述贝叶斯滤波模块500，配置为通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转所述理论自相关计算模块200；The Bayesian filtering module 500 is configured to obtain theoretical initial values and corresponding prior variances of the basic parameters of the ionosphere on all range gates at time k +1 through a Bayesian filtering method, and make k = k +1 , jumping to the theoretical autocorrelation calculation module 200;

所述贝叶斯平滑模块600，配置为通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。The Bayesian smoothing module 600 is configured to recursively smooth the basic parameters of the ionosphere and the corresponding error covariance matrix fitted on each range gate at all times within the set time period through the Bayesian smoothing algorithm to obtain the final Inversion of basic parameters of the ionosphere.

所述技术领域的技术人员可以清楚的了解到，为描述的方便和简洁，上述描述的系统的具体的工作过程及有关说明，可以参考前述方法实施例中的对应过程，在此不再赘述。Those skilled in the technical field can clearly understand that for the convenience and brevity of the description, the specific working process and relevant descriptions of the above-described system can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here.

需要说明的是，上述实施例提供的基于贝叶斯滤波的非相干散射电离层参量反演系统，仅以上述各功能模块的划分进行举例说明，在实际应用中，可以根据需要而将上述功能分配由不同的功能模块来完成，即将本发明实施例中的模块或者步骤再分解或者组合，例如，上述实施例的模块可以合并为一个模块，也可以进一步拆分成多个子模块，以完成以上描述的全部或者部分功能。对于本发明实施例中涉及的模块、步骤的名称，仅仅是为了区分各个模块或者步骤，不视为对本发明的不当限定。It should be noted that the incoherent scattering ionospheric parameter inversion system based on Bayesian filtering provided by the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be combined as required. The allocation is done by different functional modules, that is, the modules or steps in the embodiments of the present invention are decomposed or combined. For example, the modules in the above embodiments can be combined into one module, or can be further split into multiple sub-modules to complete the above All or part of the functionality described. The names of the modules and steps involved in the embodiments of the present invention are only used to distinguish each module or step, and are not regarded as improperly limiting the present invention.

本发明第三实施例的一种存储装置，其中存储有多条程序，所述程序适用于由处理器加载并实现上述的基于贝叶斯滤波的非相干散射电离层参量反演方法。A storage device according to the third embodiment of the present invention stores a plurality of programs, and the programs are suitable for being loaded by a processor to realize the above-mentioned incoherent scattering ionospheric parameter inversion method based on Bayesian filtering.

本发明第四实施例的一种处理装置，包括处理器、存储装置；处理器，适于执行各条程序；存储装置，适于存储多条程序；所述程序适于由处理器加载并执行以实现上述的基于贝叶斯滤波的非相干散射电离层参量反演方法。A processing device according to the fourth embodiment of the present invention includes a processor and a storage device; the processor is suitable for executing various programs; the storage device is suitable for storing multiple programs; the program is suitable for being loaded and executed by the processor In order to realize the above inversion method of incoherent scattering ionospheric parameters based on Bayesian filtering.

所述技术领域的技术人员可以清楚的了解到，为描述的方便和简洁，上述描述的存储装置、处理装置的具体工作过程及有关说明，可以参考前述方法实例中的对应过程，在此不再赘述。Those skilled in the technical field can clearly understand that for the convenience and brevity of the description, the specific working process and related instructions of the storage device and the processing device described above can refer to the corresponding process in the aforementioned method examples, and will not be repeated here. repeat.

下面参考图6，其示出了适于用来实现本申请方法、系统、装置实施例的服务器的计算机系统的结构示意图。图6示出的服务器仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。Referring now to FIG. 6 , it shows a schematic structural diagram of a server computer system suitable for implementing the method, system, and device embodiments of the present application. The server shown in FIG. 6 is only an example, and should not limit the functions and scope of use of this embodiment of the present application.

如图6所示，计算机系统包括中央处理单元(CPU，Central Processing Unit)601，其可以根据存储在只读存储器(ROM，Read Only Memory)602中的程序或者从存储部分608加载到随机访问存储器(RAM，Random Access Memory)603中的程序而执行各种适当的动作和处理。在RAM 603中，还存储有系统操作所需的各种程序和数据。CPU601、ROM 602以及RAM603通过总线604彼此相连。输入/输出(I/O，Input/Output)接口605也连接至总线604。As shown in Figure 6, the computer system includes a central processing unit (CPU, Central Processing Unit) 601, which can be stored in a program in a read-only memory (ROM, Read Only Memory) 602 or loaded into a random access memory from a storage section 608 (RAM, Random Access Memory) 603 to execute various appropriate actions and processes. In the RAM 603, various programs and data necessary for system operation are also stored. The CPU 601 , ROM 602 , and RAM 603 are connected to each other via a bus 604 . An input/output (I/O, Input/Output) interface 605 is also connected to the bus 604 .

以下部件连接至I/O接口605：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT，Cathode Ray Tube)、液晶显示器(LCD，Liquid Crystal Display)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN(局域网，Local AreaNetwork)卡、调制解调器等的网络接口卡的通讯部分609。通讯部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。The following components are connected to the I/O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT, Cathode Ray Tube), a liquid crystal display (LCD, Liquid Crystal Display), etc., and a speaker ; a storage section 608 including a hard disk or the like; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc. is mounted on the drive 610 as necessary so that a computer program read therefrom is installed into the storage section 608 as necessary.

特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通讯部分609从网络上被下载和安装，和/或从可拆卸介质611被安装。在该计算机程序被中央处理单元(CPU601执行时，执行本申请的方法中限定的上述功能。需要说明的是，本申请上述的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 609 and/or installed from a removable medium 611 . When the computer program is executed by the central processing unit (CPU601), the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer-readable medium mentioned above in the present application can be a computer-readable signal medium or a computer-readable storage medium Or any combination of the above two. Computer-readable storage media can be, for example—but not limited to—electric, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any combination of the above. Computer More specific examples of readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer diskettes, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable Read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In this application, the computer-readable storage medium can be Is any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can be included in the baseband or propagated as part of a carrier wave A data signal, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media can also Any computer-readable medium, other than a computer-readable storage medium, that can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. Contained on a computer-readable medium Program code may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber cable, RF, etc., or any suitable combination of the above.

可以以一种或多种程序设计语言或其组合来编写用于执行本申请的操作的计算机程序代码，上述程序设计语言包括面向对象的程序设计语言—诸如Java、Smalltalk、C++，还包括常规的过程式程序设计语言—诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络——包括局域网(LAN)或广域网(WAN)—连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof, including object-oriented programming languages—such as Java, Smalltalk, C++, and conventional Procedural Programming Language - such as "C" or a similar programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as through an Internet service provider). Internet connection).

附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，该模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logical functions for implementing specified executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.

术语“第一”、 “第二”等是用于区别类似的对象，而不是用于描述或表示特定的顺序或先后次序。The terms "first", "second", etc. are used to distinguish similar items, and are not used to describe or represent a specific order or sequence.

术语“包括”或者任何其它类似用语旨在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备/装置不仅包括那些要素，而且还包括没有明确列出的其它要素，或者还包括这些过程、方法、物品或者设备/装置所固有的要素。The term "comprising" or any other similar term is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus/apparatus comprising a set of elements includes not only those elements but also other elements not expressly listed, or Also included are elements inherent in these processes, methods, articles, or devices/devices.

至此，已经结合附图所示的优选实施方式描述了本发明的技术方案，但是，本领域技术人员容易理解的是，本发明的保护范围显然不局限于这些具体实施方式。在不偏离本发明的原理的前提下，本领域技术人员可以对相关技术特征作出等同的更改或替换，这些更改或替换之后的技术方案都将落入本发明的保护范围之内。So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings, but those skilled in the art will easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims (9)

1.一种基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，该方法包括：1. a kind of incoherent scattering ionospheric parameter inversion method based on Bayesian filter, it is characterized in that, this method comprises: 步骤S100，根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；Step S100, according to the IRI ionospheric model, obtain the theoretical initial values of the basic parameters of the ionosphere on all range gates at time k and their corresponding prior variances; when initializing at time k , it is the actual measurement used in the first fitting The actual moment corresponding to the autocorrelation data; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity; 步骤S200，基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；Step S200, based on the theoretical initial values of the basic parameters of the ionosphere on each range gate at time k , calculate the theoretical spectrum on each range gate through the theoretical model of scattering spectrum, and inverse Fourier transform the theoretical spectrum on each range gate Transform to get theoretical autocorrelation data; 步骤S300，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；Step S300, for each range gate, perform a nonlinear least squares operation on the corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters fitted on each range gate at time k and the corresponding error covariance matrix ; 步骤S400，判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转步骤S600；否则跳转步骤S500；Step S400, judging whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, if so, skip to step S600; otherwise, skip to step S500; 步骤S500，通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转步骤S200；Step S500, obtain the theoretical initial values and the corresponding prior variances of the basic parameters of the ionosphere on all range gates at time k +1 through the Bayesian filtering method, and set k = k +1, and jump to step S200; 步骤S600，通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。In step S600, recursive smoothing is performed on the ionospheric basic parameters and the corresponding error covariance matrix fitted on each range gate at all times within the set time period by Bayesian smoothing algorithm to obtain the final inverted ionospheric basic parameters. 2.根据权利要求1所述的基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，实测自相关数据与理论自相关数据之间的关系为：2. the incoherent scattering ionospheric parameter inversion method based on Bayesian filter according to claim 1, is characterized in that, the relation between measured autocorrelation data and theoretical autocorrelation data is:
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 其中，
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、
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为雷达接收机实测的原始复信号回波序列，
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为时延值，
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为由原始信号计算得到的非相干散射回波信号自相关，即实测自相关数据，
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为雷达接收机阻抗，
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为雷达发射功率，
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为从雷达天线到散射点的距离，
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、电子温度
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is the original complex signal echo sequence measured by the radar receiver,
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is the autocorrelation of the incoherent scattered echo signal calculated from the original signal, that is, the measured autocorrelation data,
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is the radar receiver impedance,
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is the radar transmit power,
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is the distance from the radar antenna to the scattering point,
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, Plasma line-of-sight drift speed
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The theoretical autocorrelation data of the determined plasma,
Figure DEST_PATH_IMAGE017
are system constants related to radar antenna gain and radar cross section. 3.根据权利要求1所述的基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到各距离门上拟合的电离层基本参量，其方法为：3. the incoherent scattering ionospheric parameter inversion method based on Bayesian filtering according to claim 1, is characterized in that, for each range gate, its corresponding measured autocorrelation data and theoretical autocorrelation data are nonlinearly The least square operation is used to obtain the basic parameters of the ionosphere fitted on each range gate, and the method is as follows: 根据设定的距离门步进间隔，逐个高度对各距离门对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，进而得到各距离门上拟合的电离层基本参量。According to the set range gate step interval, the measured autocorrelation data corresponding to each range gate and the theoretical autocorrelation data are subjected to nonlinear least squares operation height by altitude, and then the basic parameters of the ionosphere fitted on each range gate are obtained. 4.根据权利要求3所述的基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，在非相干散射雷达探测中，若采用交替码作为雷达发射信号，则将时延剖面矩阵各探测距离上的最小的时延积去掉，不参与实测自相关数据的距离门的拟合。4. the incoherent scatter ionospheric parameter inversion method based on Bayesian filter according to claim 3, is characterized in that, in incoherent scatter radar detection, if adopt alternate code as radar transmission signal, then time delay The minimum delay product at each detection distance of the profile matrix is removed, and does not participate in the fitting of the range gate of the measured autocorrelation data. 5.根据权利要求1所述的基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，每个距离门处对应的误差协方差矩阵，其获取方法为：5. the incoherent scattering ionospheric parameter inversion method based on Bayesian filter according to claim 1, is characterized in that, the corresponding error covariance matrix at each range gate place, its acquisition method is:
Figure 801918DEST_PATH_IMAGE018
Figure 801918DEST_PATH_IMAGE018
 其中，
Figure DEST_PATH_IMAGE019
为误差协方差矩阵，
Figure 103718DEST_PATH_IMAGE020
为拟合残差一阶偏导，
Figure DEST_PATH_IMAGE021
为实测自相关数据的方差，T表示转置。in,
Figure DEST_PATH_IMAGE019
is the error covariance matrix,
Figure 103718DEST_PATH_IMAGE020
For the first partial derivative of the fitted residual,
Figure DEST_PATH_IMAGE021
is the variance of the measured autocorrelation data, and T represents the transpose. 6.根据权利要求5所述的基于贝叶斯滤波的非相干散射电离层参量反演方法，其特征在于，通过贝叶斯滤波方法获取k+1时刻所有距离门上的初始基本参量，其方法为：6. the incoherent scattering ionospheric parameter inversion method based on Bayesian filtering according to claim 5, is characterized in that, obtains the initial basic parameter on all range gates of k +1 moment by Bayesian filtering method, its The method is: 若未知的电离层基本参量x的先验值
Figure 371888DEST_PATH_IMAGE022
为真值，电离层基本参量x与其对应的理论初值的映射关系为
Figure DEST_PATH_IMAGE023
，先验方差为
Figure 692011DEST_PATH_IMAGE024
，则它们之间的线性关系为：If the unknown prior value of the basic ionospheric parameter x
Figure 371888DEST_PATH_IMAGE022
is the true value, the mapping relationship between the basic ionospheric parameter x and its corresponding theoretical initial value is
Figure DEST_PATH_IMAGE023
, the prior variance is
Figure 692011DEST_PATH_IMAGE024
, then the linear relationship between them is:
Figure DEST_PATH_IMAGE025
Figure DEST_PATH_IMAGE025
 将
Figure 934904DEST_PATH_IMAGE026
、
Figure DEST_PATH_IMAGE027
分别以最大二阶差分形式展开：Will
Figure 934904DEST_PATH_IMAGE026
,
Figure DEST_PATH_IMAGE027
Expand respectively in the form of maximum second-order differences:
Figure 973268DEST_PATH_IMAGE028
，
Figure DEST_PATH_IMAGE029
Figure 973268DEST_PATH_IMAGE028
,
Figure DEST_PATH_IMAGE029
 其中，
Figure 58511DEST_PATH_IMAGE030
、
Figure DEST_PATH_IMAGE031
、
Figure 498719DEST_PATH_IMAGE032
分别表示第零阶、第一阶、第二阶的先验方差；in,
Figure 58511DEST_PATH_IMAGE030
,
Figure DEST_PATH_IMAGE031
,
Figure 498719DEST_PATH_IMAGE032
Respectively represent the prior variance of the zeroth order, first order, and second order; 对于每个电离层基本参量，第零阶的差分矩阵为单位矩阵，即
Figure DEST_PATH_IMAGE033
，第一阶和第二阶差分矩阵
Figure 630623DEST_PATH_IMAGE034
、
Figure DEST_PATH_IMAGE035
分别为
Figure 907015DEST_PATH_IMAGE036
和
Figure DEST_PATH_IMAGE037
的矩阵形式，表示为：For each basic ionospheric parameter, the difference matrix of the zeroth order is the identity matrix, namely
Figure DEST_PATH_IMAGE033
, the first-order and second-order difference matrices
Figure 630623DEST_PATH_IMAGE034
,
Figure DEST_PATH_IMAGE035
respectively
Figure 907015DEST_PATH_IMAGE036
and
Figure DEST_PATH_IMAGE037
In matrix form, expressed as:
Figure 782567DEST_PATH_IMAGE038
，
Figure DEST_PATH_IMAGE039
Figure 782567DEST_PATH_IMAGE038
,
Figure DEST_PATH_IMAGE039
 其中，
Figure 77282DEST_PATH_IMAGE040
表示距离门个数；in,
Figure 77282DEST_PATH_IMAGE040
Indicates the number of range gates; 前一时刻拟合获得的所有距离门上的误差协方差矩阵可以作为第零阶协方差矩阵，由此可以进一步推导得到第一阶和第二阶协方差矩阵，分别为The error covariance matrix on all range gates obtained by fitting at the previous moment can be used as the zeroth-order covariance matrix, and the first-order and second-order covariance matrices can be further derived, respectively,
Figure DEST_PATH_IMAGE041
Figure DEST_PATH_IMAGE041
 其中，
Figure 396399DEST_PATH_IMAGE042
为取对角线，
Figure DEST_PATH_IMAGE043
为距离门步进间隔，
Figure 409355DEST_PATH_IMAGE044
为每个参数的相关长度，正比于等离子体标高
Figure DEST_PATH_IMAGE045
，
Figure 636068DEST_PATH_IMAGE046
为常量，
Figure DEST_PATH_IMAGE047
表示k时刻第
Figure 939617DEST_PATH_IMAGE040
个距离门的协方差矩阵；in,
Figure 396399DEST_PATH_IMAGE042
To take the diagonal,
Figure DEST_PATH_IMAGE043
is the stepping interval of the range gate,
Figure 409355DEST_PATH_IMAGE044
is the correlation length for each parameter, proportional to the plasma elevation
Figure DEST_PATH_IMAGE045
,
Figure 636068DEST_PATH_IMAGE046
as a constant,
Figure DEST_PATH_IMAGE047
Indicates that the kth time
Figure 939617DEST_PATH_IMAGE040
covariance matrix of range gates; 运用最小二乘思想计算
Figure 147744DEST_PATH_IMAGE048
达到最小，那么从上述的线性关系的公式可得到：Using the least squares thinking to calculate
Figure 147744DEST_PATH_IMAGE048
Reaching the minimum, then from the above linear relationship formula can be obtained:
Figure DEST_PATH_IMAGE049
Figure DEST_PATH_IMAGE049
 其中，
Figure 913575DEST_PATH_IMAGE050
为贝叶斯滤波后的参数剖面，
Figure 616083DEST_PATH_IMAGE051
为贝叶斯滤波后的协方差矩阵，T表示转置；因此基于贝叶斯滤波后下一时刻电离层基本参量的理论初值
Figure 619811DEST_PATH_IMAGE052
和对应的先验方差
Figure DEST_PATH_IMAGE053
分别为in,
Figure 913575DEST_PATH_IMAGE050
is the parameter profile after Bayesian filtering,
Figure 616083DEST_PATH_IMAGE051
is the covariance matrix after Bayesian filtering, and T represents the transpose; therefore, based on the theoretical initial value of the basic parameters of the ionosphere at the next moment after Bayesian filtering
Figure 619811DEST_PATH_IMAGE052
and the corresponding prior variance
Figure DEST_PATH_IMAGE053
respectively
Figure 811889DEST_PATH_IMAGE054
Figure 811889DEST_PATH_IMAGE054
 其中，
Figure DEST_PATH_IMAGE055
为时间步进间隔，即拟合过程中的积累时间，
Figure 65016DEST_PATH_IMAGE056
为常量，
Figure DEST_PATH_IMAGE057
为过程噪声方差。in,
Figure DEST_PATH_IMAGE055
is the time step interval, that is, the accumulation time in the fitting process,
Figure 65016DEST_PATH_IMAGE056
as a constant,
Figure DEST_PATH_IMAGE057
is the process noise variance. 7.一种基于贝叶斯滤波的非相干散射电离层参量反演系统，其特征在于，该系统包括：参量初值获取模块、理论自相关计算模块、参量输出模块、循环判断模块、贝叶斯滤波模块、贝叶斯平滑模块；7. An incoherent scattering ionospheric parameter inversion system based on Bayesian filtering, characterized in that the system includes: a parameter initial value acquisition module, a theoretical autocorrelation calculation module, a parameter output module, a cyclic judgment module, a Bayesian Si filter module, Bayesian smooth module; 所述参量初值获取模块，配置为根据IRI电离层模型，获取k时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差；k时刻初始化时，为在第一次拟合时所采用的实测自相关数据对应的实际时刻；所述电离层基本参量包括电子密度、电子温度、离子温度和等离子体视线漂移速度；The parameter initial value acquisition module is configured to obtain theoretical initial values and corresponding prior variances of the ionospheric basic parameters on all range gates at time k according to the IRI ionospheric model; The actual moment corresponding to the measured autocorrelation data used during fitting; the basic parameters of the ionosphere include electron density, electron temperature, ion temperature and plasma line-of-sight drift velocity; 所述理论自相关计算模块，配置为基于k时刻各距离门上的电离层基本参量的理论初值，通过散射谱理论模型计算每个距离门上的理论谱，并将每个距离门上的理论谱进行逆傅里叶变换，得到理论自相关数据；The theoretical autocorrelation calculation module is configured to calculate the theoretical spectrum on each range gate based on the theoretical initial value of the ionospheric basic parameters on each range gate at time k , and calculate the theoretical spectrum on each range gate through the scattering spectrum theoretical model, and calculate the theoretical spectrum on each range gate. Inverse Fourier transform is performed on the theoretical spectrum to obtain theoretical autocorrelation data; 所述参量输出模块，配置为对各距离门，将其对应的实测自相关数据与理论自相关数据进行非线性最小二乘运算，得到k时刻各距离门上拟合的电离层基本参量及对应的误差协方差矩阵；The parameter output module is configured to perform a nonlinear least squares operation on each range gate with its corresponding measured autocorrelation data and theoretical autocorrelation data, and obtain the ionospheric basic parameters and corresponding The error covariance matrix of ; 所述循环判断模块，配置为判断是否拟合完设定时间段内所有时刻各距离门上的电离层基本参量及对应的误差协方差矩阵，若是，则跳转所述贝叶斯平滑模块；否则跳转所述贝叶斯滤波模块；The loop judgment module is configured to judge whether the basic parameters of the ionosphere and the corresponding error covariance matrix on each range gate at all times within the set time period have been fitted, and if so, jump to the Bayesian smoothing module; Otherwise, jump to the Bayesian filtering module; 所述贝叶斯滤波模块，配置为通过贝叶斯滤波方法获取k+1时刻所有距离门上的电离层基本参量的理论初值及其对应的先验方差，并令k= k+1，跳转所述理论自相关计算模块；The Bayesian filtering module is configured to obtain theoretical initial values and corresponding prior variances of the ionospheric basic parameters on all range gates at k +1 moment by Bayesian filtering method, and make k = k +1, Jump to the theoretical autocorrelation calculation module; 所述贝叶斯平滑模块，配置为通过贝叶斯平滑算法对设定时间段内所有时刻各距离门上拟合的电离层基本参量以及对应的误差协方差矩阵进行递归平滑处理，得到最终反演的电离层基本参量。The Bayesian smoothing module is configured to recursively smooth the basic parameters of the ionosphere and the corresponding error covariance matrix fitted on each range gate at all times within the set time period through the Bayesian smoothing algorithm to obtain the final response The basic parameters of the ionosphere. 8.一种存储装置，其中存储有多条程序，其特征在于，所述程序应用由处理器加载并执行以实现权利要求1-6任一项所述的基于贝叶斯滤波的非相干散射电离层参量反演方法。8. A storage device, wherein a plurality of programs are stored, wherein the program application is loaded and executed by a processor to realize the incoherent scattering based on Bayesian filtering described in any one of claims 1-6 Ionospheric parameter inversion method. 9.一种处理装置，包括处理器、存储装置；处理器，适用于执行各条程序；存储装置，适用于存储多条程序；其特征在于，所述程序适用于由处理器加载并执行以实现权利要求1-6任一项所述的基于贝叶斯滤波的非相干散射电离层参量反演方法。9. A processing device, comprising a processor and a storage device; the processor is suitable for executing various programs; the storage device is suitable for storing multiple programs; it is characterized in that the program is suitable for being loaded and executed by the processor The inversion method for incoherent scattering ionospheric parameters based on Bayesian filtering described in any one of claims 1-6 is realized.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
SU1171735A1 (en) * 1983-12-27 1985-08-07 Харьковский Ордена Ленина Политехнический Институт Им.В.И.Ленина Method of determining correlation function of signals which uncoherently scattered by ionosphere
CN109188475A (en) * 2018-09-20 2019-01-11 武汉大学 Region ionospheric electron density three-dimensional real-time monitoring system and method based on CORS
CN111273267A (en) * 2020-02-19 2020-06-12 中国科学院地质与地球物理研究所 Signal processing method, system and device based on phased array incoherent scattering radar

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
SU1171735A1 (en) * 1983-12-27 1985-08-07 Харьковский Ордена Ленина Политехнический Институт Им.В.И.Ленина Method of determining correlation function of signals which uncoherently scattered by ionosphere
CN109188475A (en) * 2018-09-20 2019-01-11 武汉大学 Region ionospheric electron density three-dimensional real-time monitoring system and method based on CORS
CN111273267A (en) * 2020-02-19 2020-06-12 中国科学院地质与地球物理研究所 Signal processing method, system and device based on phased array incoherent scattering radar

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Gaussian Markov Random Field Priors in Ionospheric 3-D Multi-Instrument Tomography;Johannes Norberg 等;《IEEE Transactions on Geoscience and Remote Sensing》;20180822;第56卷(第12期);全文 *
基于长短时记忆神经网络的中国地区电离层TEC预测;熊波 等;《地球物理学报》;20220731;第65卷(第07期);全文 *
电离层非相干散射雷达参数反演算法的优化与实现;熊嘉伟;《中国优秀硕士学位论文全文数据库基础科学辑》;20220315(第03期);全文 *

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